author = {Wu, Jiamin and Zhang, Tianzhu and Zha, Zheng-Jun and Luo, Jiebo and Zhang, Yongdong and Wu, Feng},
title = {Self-Supervised Domain-Aware Generative Network for Generalized Zero-Shot Learning},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Sparse Layered Graphs for Multi-Object Segmentation-
[pdf]
[bibtex]@InProceedings{Jeppesen_2020_CVPR,
author = {Jeppesen, Niels and Christensen, Anders N. and Dahl, Vedrana A. and Dahl, Anders B.},
title = {Sparse Layered Graphs for Multi-Object Segmentation},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Visual-Semantic Matching by Exploring High-Order Attention and Distraction-
[pdf]
[bibtex]@InProceedings{Li_2020_CVPR,
author = {Li, Yongzhi and Zhang, Duo and Mu, Yadong},
title = {Visual-Semantic Matching by Exploring High-Order Attention and Distraction},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
End-to-End 3D Point Cloud Instance Segmentation Without Detection-
[pdf]
[bibtex]@InProceedings{Jiang_2020_CVPR,
author = {Jiang, Haiyong and Yan, Feilong and Cai, Jianfei and Zheng, Jianmin and Xiao, Jun},
title = {End-to-End 3D Point Cloud Instance Segmentation Without Detection},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Deep Adversarial Decomposition: A Unified Framework for Separating Superimposed Images-
[pdf]
[bibtex]@InProceedings{Zou_2020_CVPR,
author = {Zou, Zhengxia and Lei, Sen and Shi, Tianyang and Shi, Zhenwei and Ye, Jieping},
title = {Deep Adversarial Decomposition: A Unified Framework for Separating Superimposed Images},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Differentiable Adaptive Computation Time for Visual Reasoning-
[pdf]
[bibtex]@InProceedings{Eyzaguirre_2020_CVPR,
author = {Eyzaguirre, Cristobal and Soto, Alvaro},
title = {Differentiable Adaptive Computation Time for Visual Reasoning},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
DeepLPF: Deep Local Parametric Filters for Image Enhancement-
[pdf]
[bibtex]@InProceedings{Moran_2020_CVPR,
author = {Moran, Sean and Marza, Pierre and McDonagh, Steven and Parisot, Sarah and Slabaugh, Gregory},
title = {DeepLPF: Deep Local Parametric Filters for Image Enhancement},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Instance Credibility Inference for Few-Shot Learning-
[pdf]
[bibtex]@InProceedings{Wang_2020_CVPR,
author = {Wang, Yikai and Xu, Chengming and Liu, Chen and Zhang, Li and Fu, Yanwei},
title = {Instance Credibility Inference for Few-Shot Learning},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Learning From Web Data With Self-Organizing Memory Module-
[pdf]
[bibtex]@InProceedings{Tu_2020_CVPR,
author = {Tu, Yi and Niu, Li and Chen, Junjie and Cheng, Dawei and Zhang, Liqing},
title = {Learning From Web Data With Self-Organizing Memory Module},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
TransMatch: A Transfer-Learning Scheme for Semi-Supervised Few-Shot Learning-
[pdf]
[bibtex]@InProceedings{Yu_2020_CVPR,
author = {Yu, Zhongjie and Chen, Lin and Cheng, Zhongwei and Luo, Jiebo},
title = {TransMatch: A Transfer-Learning Scheme for Semi-Supervised Few-Shot Learning},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Learning the Redundancy-Free Features for Generalized Zero-Shot Object Recognition-
[pdf]
[bibtex]@InProceedings{Han_2020_CVPR,
author = {Han, Zongyan and Fu, Zhenyong and Yang, Jian},
title = {Learning the Redundancy-Free Features for Generalized Zero-Shot Object Recognition},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Neural Topological SLAM for Visual Navigation-
[pdf]
[bibtex]@InProceedings{Chaplot_2020_CVPR,
author = {Chaplot, Devendra Singh and Salakhutdinov, Ruslan and Gupta, Abhinav and Gupta, Saurabh},
title = {Neural Topological SLAM for Visual Navigation},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
WaveletStereo: Learning Wavelet Coefficients of Disparity Map in Stereo Matching-
[pdf]
[bibtex]@InProceedings{Yang_2020_CVPR,
author = {Yang, Menglong and Wu, Fangrui and Li, Wei},
title = {WaveletStereo: Learning Wavelet Coefficients of Disparity Map in Stereo Matching},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Robust Superpixel-Guided Attentional Adversarial Attack-
[pdf]
[bibtex]@InProceedings{Dong_2020_CVPR,
author = {Dong, Xiaoyi and Han, Jiangfan and Chen, Dongdong and Liu, Jiayang and Bian, Huanyu and Ma, Zehua and Li, Hongsheng and Wang, Xiaogang and Zhang, Weiming and Yu, Nenghai},
title = {Robust Superpixel-Guided Attentional Adversarial Attack},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
BEDSR-Net: A Deep Shadow Removal Network From a Single Document Image-
[pdf]
[bibtex]@InProceedings{Lin_2020_CVPR,
author = {Lin, Yun-Hsuan and Chen, Wen-Chin and Chuang, Yung-Yu},
title = {BEDSR-Net: A Deep Shadow Removal Network From a Single Document Image},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Cross-Domain Document Object Detection: Benchmark Suite and Method-
[pdf]
[bibtex]@InProceedings{Li_2020_CVPR,
author = {Li, Kai and Wigington, Curtis and Tensmeyer, Chris and Zhao, Handong and Barmpalios, Nikolaos and Morariu, Vlad I. and Manjunatha, Varun and Sun, Tong and Fu, Yun},
title = {Cross-Domain Document Object Detection: Benchmark Suite and Method},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Explaining Knowledge Distillation by Quantifying the Knowledge-
[pdf]
[bibtex]@InProceedings{Cheng_2020_CVPR,
author = {Cheng, Xu and Rao, Zhefan and Chen, Yilan and Zhang, Quanshi},
title = {Explaining Knowledge Distillation by Quantifying the Knowledge},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Exploring Bottom-Up and Top-Down Cues With Attentive Learning for Webly Supervised Object Detection-
[pdf]
[bibtex]@InProceedings{Wu_2020_CVPR,
author = {Wu, Zhonghua and Tao, Qingyi and Lin, Guosheng and Cai, Jianfei},
title = {Exploring Bottom-Up and Top-Down Cues With Attentive Learning for Webly Supervised Object Detection},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Enhancing Generic Segmentation With Learned Region Representations-
[pdf]
[bibtex]@InProceedings{Isaacs_2020_CVPR,
author = {Isaacs, Or and Shayer, Oran and Lindenbaum, Michael},
title = {Enhancing Generic Segmentation With Learned Region Representations},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Adaptive Hierarchical Down-Sampling for Point Cloud Classification-
[pdf]
[bibtex]@InProceedings{Nezhadarya_2020_CVPR,
author = {Nezhadarya, Ehsan and Taghavi, Ehsan and Razani, Ryan and Liu, Bingbing and Luo, Jun},
title = {Adaptive Hierarchical Down-Sampling for Point Cloud Classification},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
FBNetV2: Differentiable Neural Architecture Search for Spatial and Channel Dimensions-
[pdf]
[bibtex]@InProceedings{Wan_2020_CVPR,
author = {Wan, Alvin and Dai, Xiaoliang and Zhang, Peizhao and He, Zijian and Tian, Yuandong and Xie, Saining and Wu, Bichen and Yu, Matthew and Xu, Tao and Chen, Kan and Vajda, Peter and Gonzalez, Joseph E.},
title = {FBNetV2: Differentiable Neural Architecture Search for Spatial and Channel Dimensions},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Learning Texture Invariant Representation for Domain Adaptation of Semantic Segmentation-
[pdf]
[bibtex]@InProceedings{Kim_2020_CVPR,
author = {Kim, Myeongjin and Byun, Hyeran},
title = {Learning Texture Invariant Representation for Domain Adaptation of Semantic Segmentation},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Putting Visual Object Recognition in Context-
[pdf]
[bibtex]@InProceedings{Zhang_2020_CVPR,
author = {Zhang, Mengmi and Tseng, Claire and Kreiman, Gabriel},
title = {Putting Visual Object Recognition in Context},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
SLV: Spatial Likelihood Voting for Weakly Supervised Object Detection-
[pdf]
[bibtex]@InProceedings{Chen_2020_CVPR,
author = {Chen, Ze and Fu, Zhihang and Jiang, Rongxin and Chen, Yaowu and Hua, Xian-Sheng},
title = {SLV: Spatial Likelihood Voting for Weakly Supervised Object Detection},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Universal Weighting Metric Learning for Cross-Modal Matching-
[pdf]
[bibtex]@InProceedings{Wei_2020_CVPR,
author = {Wei, Jiwei and Xu, Xing and Yang, Yang and Ji, Yanli and Wang, Zheng and Shen, Heng Tao},
title = {Universal Weighting Metric Learning for Cross-Modal Matching},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
IDA-3D: Instance-Depth-Aware 3D Object Detection From Stereo Vision for Autonomous Driving-
[pdf]
[bibtex]@InProceedings{Peng_2020_CVPR,
author = {Peng, Wanli and Pan, Hao and Liu, He and Sun, Yi},
title = {IDA-3D: Instance-Depth-Aware 3D Object Detection From Stereo Vision for Autonomous Driving},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Label Decoupling Framework for Salient Object Detection-
[pdf]
[bibtex]@InProceedings{Wei_2020_CVPR,
author = {Wei, Jun and Wang, Shuhui and Wu, Zhe and Su, Chi and Huang, Qingming and Tian, Qi},
title = {Label Decoupling Framework for Salient Object Detection},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Transform and Tell: Entity-Aware News Image Captioning-
[pdf]
[bibtex]@InProceedings{Tran_2020_CVPR,
author = {Tran, Alasdair and Mathews, Alexander and Xie, Lexing},
title = {Transform and Tell: Entity-Aware News Image Captioning},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
HAMBox: Delving Into Mining High-Quality Anchors on Face Detection-
[pdf]
[bibtex]@InProceedings{Liu_2020_CVPR,
author = {Liu, Yang and Tang, Xu and Han, Junyu and Liu, Jingtuo and Rui, Dinger and Wu, Xiang},
title = {HAMBox: Delving Into Mining High-Quality Anchors on Face Detection},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Hierarchical Feature Embedding for Attribute Recognition-
[pdf]
[bibtex]@InProceedings{Yang_2020_CVPR,
author = {Yang, Jie and Fan, Jiarou and Wang, Yiru and Wang, Yige and Gan, Weihao and Liu, Lin and Wu, Wei},
title = {Hierarchical Feature Embedding for Attribute Recognition},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Squeeze-and-Attention Networks for Semantic Segmentation-
[pdf]
[bibtex]@InProceedings{Zhong_2020_CVPR,
author = {Zhong, Zilong and Lin, Zhong Qiu and Bidart, Rene and Hu, Xiaodan and Daya, Ibrahim Ben and Li, Zhifeng and Zheng, Wei-Shi and Li, Jonathan and Wong, Alexander},
title = {Squeeze-and-Attention Networks for Semantic Segmentation},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Context R-CNN: Long Term Temporal Context for Per-Camera Object Detection-
[pdf]
[bibtex]@InProceedings{Beery_2020_CVPR,
author = {Beery, Sara and Wu, Guanhang and Rathod, Vivek and Votel, Ronny and Huang, Jonathan},
title = {Context R-CNN: Long Term Temporal Context for Per-Camera Object Detection},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Mixture Dense Regression for Object Detection and Human Pose Estimation-
[pdf]
[bibtex]@InProceedings{Varamesh_2020_CVPR,
author = {Varamesh, Ali and Tuytelaars, Tinne},
title = {Mixture Dense Regression for Object Detection and Human Pose Estimation},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Syntax-Aware Action Targeting for Video Captioning-
[pdf]
[bibtex]@InProceedings{Zheng_2020_CVPR,
author = {Zheng, Qi and Wang, Chaoyue and Tao, Dacheng},
title = {Syntax-Aware Action Targeting for Video Captioning},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Learning Visual Emotion Representations From Web Data-
[pdf]
[bibtex]@InProceedings{Wei_2020_CVPR,
author = {Wei, Zijun and Zhang, Jianming and Lin, Zhe and Lee, Joon-Young and Balasubramanian, Niranjan and Hoai, Minh and Samaras, Dimitris},
title = {Learning Visual Emotion Representations From Web Data},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
The Edge of Depth: Explicit Constraints Between Segmentation and Depth-
[pdf]
[bibtex]@InProceedings{Zhu_2020_CVPR,
author = {Zhu, Shengjie and Brazil, Garrick and Liu, Xiaoming},
title = {The Edge of Depth: Explicit Constraints Between Segmentation and Depth},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
A Context-Aware Loss Function for Action Spotting in Soccer Videos-
[pdf]
[bibtex]@InProceedings{Cioppa_2020_CVPR,
author = {Cioppa, Anthony and Deliege, Adrien and Giancola, Silvio and Ghanem, Bernard and Droogenbroeck, Marc Van and Gade, Rikke and Moeslund, Thomas B.},
title = {A Context-Aware Loss Function for Action Spotting in Soccer Videos},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Towards Learning a Generic Agent for Vision-and-Language Navigation via Pre-Training-
[pdf]
[bibtex]@InProceedings{Hao_2020_CVPR,
author = {Hao, Weituo and Li, Chunyuan and Li, Xiujun and Carin, Lawrence and Gao, Jianfeng},
title = {Towards Learning a Generic Agent for Vision-and-Language Navigation via Pre-Training},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Video Instance Segmentation Tracking With a Modified VAE Architecture-
[pdf]
[bibtex]@InProceedings{Lin_2020_CVPR,
author = {Lin, Chung-Ching and Hung, Ying and Feris, Rogerio and He, Linglin},
title = {Video Instance Segmentation Tracking With a Modified VAE Architecture},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Deformation-Aware Unpaired Image Translation for Pose Estimation on Laboratory Animals-
[pdf]
[bibtex]@InProceedings{Li_2020_CVPR,
author = {Li, Siyuan and Gunel, Semih and Ostrek, Mirela and Ramdya, Pavan and Fua, Pascal and Rhodin, Helge},
title = {Deformation-Aware Unpaired Image Translation for Pose Estimation on Laboratory Animals},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
ZeroQ: A Novel Zero Shot Quantization Framework-
[pdf]
[bibtex]@InProceedings{Cai_2020_CVPR,
author = {Cai, Yaohui and Yao, Zhewei and Dong, Zhen and Gholami, Amir and Mahoney, Michael W. and Keutzer, Kurt},
title = {ZeroQ: A Novel Zero Shot Quantization Framework},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Disparity-Aware Domain Adaptation in Stereo Image Restoration-
[pdf]
[bibtex]@InProceedings{Yan_2020_CVPR,
author = {Yan, Bo and Ma, Chenxi and Bare, Bahetiyaer and Tan, Weimin and Hoi, Steven C. H.},
title = {Disparity-Aware Domain Adaptation in Stereo Image Restoration},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Offset Bin Classification Network for Accurate Object Detection-
[pdf]
[bibtex]@InProceedings{Qiu_2020_CVPR,
author = {Qiu, Heqian and Li, Hongliang and Wu, Qingbo and Shi, Hengcan},
title = {Offset Bin Classification Network for Accurate Object Detection},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
TBT: Targeted Neural Network Attack With Bit Trojan-
[pdf]
[bibtex]@InProceedings{Rakin_2020_CVPR,
author = {Rakin, Adnan Siraj and He, Zhezhi and Fan, Deliang},
title = {TBT: Targeted Neural Network Attack With Bit Trojan},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Maintaining Discrimination and Fairness in Class Incremental Learning-
[pdf]
[bibtex]@InProceedings{Zhao_2020_CVPR,
author = {Zhao, Bowen and Xiao, Xi and Gan, Guojun and Zhang, Bin and Xia, Shu-Tao},
title = {Maintaining Discrimination and Fairness in Class Incremental Learning},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Background Data Resampling for Outlier-Aware Classification-
[pdf]
[bibtex]@InProceedings{Li_2020_CVPR,
author = {Li, Yi and Vasconcelos, Nuno},
title = {Background Data Resampling for Outlier-Aware Classification},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
STEFANN: Scene Text Editor Using Font Adaptive Neural Network-
[pdf]
[bibtex]@InProceedings{Roy_2020_CVPR,
author = {Roy, Prasun and Bhattacharya, Saumik and Ghosh, Subhankar and Pal, Umapada},
title = {STEFANN: Scene Text Editor Using Font Adaptive Neural Network},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Geometry and Learning Co-Supported Normal Estimation for Unstructured Point Cloud-
[pdf]
[bibtex]@InProceedings{Zhou_2020_CVPR,
author = {Zhou, Haoran and Chen, Honghua and Feng, Yidan and Wang, Qiong and Qin, Jing and Xie, Haoran and Wang, Fu Lee and Wei, Mingqiang and Wang, Jun},
title = {Geometry and Learning Co-Supported Normal Estimation for Unstructured Point Cloud},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Sequential Motif Profiles and Topological Plots for Offline Signature Verification-
[pdf]
[bibtex]@InProceedings{Zois_2020_CVPR,
author = {Zois, Elias N. and Zervas, Evangelos and Tsourounis, Dimitrios and Economou, George},
title = {Sequential Motif Profiles and Topological Plots for Offline Signature Verification},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Optical Flow in Dense Foggy Scenes Using Semi-Supervised Learning-
[pdf]
[bibtex]@InProceedings{Yan_2020_CVPR,
author = {Yan, Wending and Sharma, Aashish and Tan, Robby T.},
title = {Optical Flow in Dense Foggy Scenes Using Semi-Supervised Learning},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
A Spatial RNN Codec for End-to-End Image Compression-
[pdf]
[bibtex]@InProceedings{Lin_2020_CVPR,
author = {Lin, Chaoyi and Yao, Jiabao and Chen, Fangdong and Wang, Li},
title = {A Spatial RNN Codec for End-to-End Image Compression},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Object Relational Graph With Teacher-Recommended Learning for Video Captioning-
[pdf]
[bibtex]@InProceedings{Zhang_2020_CVPR,
author = {Zhang, Ziqi and Shi, Yaya and Yuan, Chunfeng and Li, Bing and Wang, Peijin and Hu, Weiming and Zha, Zheng-Jun},
title = {Object Relational Graph With Teacher-Recommended Learning for Video Captioning},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
MMTM: Multimodal Transfer Module for CNN Fusion-
[pdf]
[bibtex]@InProceedings{Joze_2020_CVPR,
author = {Joze, Hamid Reza Vaezi and Shaban, Amirreza and Iuzzolino, Michael L. and Koishida, Kazuhito},
title = {MMTM: Multimodal Transfer Module for CNN Fusion},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Generalized Zero-Shot Learning via Over-Complete Distribution-
[pdf]
[bibtex]@InProceedings{Keshari_2020_CVPR,
author = {Keshari, Rohit and Singh, Richa and Vatsa, Mayank},
title = {Generalized Zero-Shot Learning via Over-Complete Distribution},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Gait Recognition via Semi-supervised Disentangled Representation Learning to Identity and Covariate Features-
[pdf]
[bibtex]@InProceedings{Li_2020_CVPR,
author = {Li, Xiang and Makihara, Yasushi and Xu, Chi and Yagi, Yasushi and Ren, Mingwu},
title = {Gait Recognition via Semi-supervised Disentangled Representation Learning to Identity and Covariate Features},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Unifying Training and Inference for Panoptic Segmentation-
[pdf]
[bibtex]@InProceedings{Li_2020_CVPR,
author = {Li, Qizhu and Qi, Xiaojuan and Torr, Philip H.S.},
title = {Unifying Training and Inference for Panoptic Segmentation},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Associate-3Ddet: Perceptual-to-Conceptual Association for 3D Point Cloud Object Detection-
[pdf]
[bibtex]@InProceedings{Du_2020_CVPR,
author = {Du, Liang and Ye, Xiaoqing and Tan, Xiao and Feng, Jianfeng and Xu, Zhenbo and Ding, Errui and Wen, Shilei},
title = {Associate-3Ddet: Perceptual-to-Conceptual Association for 3D Point Cloud Object Detection},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Interactive Image Segmentation With First Click Attention-
[pdf]
[bibtex]@InProceedings{Lin_2020_CVPR,
author = {Lin, Zheng and Zhang, Zhao and Chen, Lin-Zhuo and Cheng, Ming-Ming and Lu, Shao-Ping},
title = {Interactive Image Segmentation With First Click Attention},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
NETNet: Neighbor Erasing and Transferring Network for Better Single Shot Object Detection-
[pdf]
[bibtex]@InProceedings{Li_2020_CVPR,
author = {Li, Yazhao and Pang, Yanwei and Shen, Jianbing and Cao, Jiale and Shao, Ling},
title = {NETNet: Neighbor Erasing and Transferring Network for Better Single Shot Object Detection},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Scale-Equalizing Pyramid Convolution for Object Detection-
[pdf]
[bibtex]@InProceedings{Wang_2020_CVPR,
author = {Wang, Xinjiang and Zhang, Shilong and Yu, Zhuoran and Feng, Litong and Zhang, Wayne},
title = {Scale-Equalizing Pyramid Convolution for Object Detection},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Learning to Cluster Faces via Confidence and Connectivity Estimation-
[pdf]
[bibtex]@InProceedings{Yang_2020_CVPR,
author = {Yang, Lei and Chen, Dapeng and Zhan, Xiaohang and Zhao, Rui and Loy, Chen Change and Lin, Dahua},
title = {Learning to Cluster Faces via Confidence and Connectivity Estimation},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Cross-Modality Person Re-Identification With Shared-Specific Feature Transfer-
[pdf]
[bibtex]@InProceedings{Lu_2020_CVPR,
author = {Lu, Yan and Wu, Yue and Liu, Bin and Zhang, Tianzhu and Li, Baopu and Chu, Qi and Yu, Nenghai},
title = {Cross-Modality Person Re-Identification With Shared-Specific Feature Transfer},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
DPGN: Distribution Propagation Graph Network for Few-Shot Learning-
[pdf]
[bibtex]@InProceedings{Yang_2020_CVPR,
author = {Yang, Ling and Li, Liangliang and Zhang, Zilun and Zhou, Xinyu and Zhou, Erjin and Liu, Yu},
title = {DPGN: Distribution Propagation Graph Network for Few-Shot Learning},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Density-Aware Graph for Deep Semi-Supervised Visual Recognition-
[pdf]
[bibtex]@InProceedings{Li_2020_CVPR,
author = {Li, Suichan and Liu, Bin and Chen, Dongdong and Chu, Qi and Yuan, Lu and Yu, Nenghai},
title = {Density-Aware Graph for Deep Semi-Supervised Visual Recognition},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Unsupervised Multi-Modal Image Registration via Geometry Preserving Image-to-Image Translation-
[pdf]
[bibtex]@InProceedings{Arar_2020_CVPR,
author = {Arar, Moab and Ginger, Yiftach and Danon, Dov and Bermano, Amit H. and Cohen-Or, Daniel},
title = {Unsupervised Multi-Modal Image Registration via Geometry Preserving Image-to-Image Translation},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Binarizing MobileNet via Evolution-Based Searching-
[pdf]
[bibtex]@InProceedings{Phan_2020_CVPR,
author = {Phan, Hai and Liu, Zechun and Huynh, Dang and Savvides, Marios and Cheng, Kwang-Ting and Shen, Zhiqiang},
title = {Binarizing MobileNet via Evolution-Based Searching},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Temporal-Context Enhanced Detection of Heavily Occluded Pedestrians-
[pdf]
[bibtex]@InProceedings{Wu_2020_CVPR,
author = {Wu, Jialian and Zhou, Chunluan and Yang, Ming and Zhang, Qian and Li, Yuan and Yuan, Junsong},
title = {Temporal-Context Enhanced Detection of Heavily Occluded Pedestrians},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Orderless Recurrent Models for Multi-Label Classification-
[pdf]
[bibtex]@InProceedings{Yazici_2020_CVPR,
author = {Yazici, Vacit Oguz and Gonzalez-Garcia, Abel and Ramisa, Arnau and Twardowski, Bartlomiej and Weijer, Joost van de},
title = {Orderless Recurrent Models for Multi-Label Classification},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Gold Seeker: Information Gain From Policy Distributions for Goal-Oriented Vision-and-Langauge Reasoning-
[pdf]
[bibtex]@InProceedings{Abbasnejad_2020_CVPR,
author = {Abbasnejad, Ehsan and Abbasnejad, Iman and Wu, Qi and Shi, Javen and Hengel, Anton van den},
title = {Gold Seeker: Information Gain From Policy Distributions for Goal-Oriented Vision-and-Langauge Reasoning},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Rethinking the Route Towards Weakly Supervised Object Localization-
[pdf]
[bibtex]@InProceedings{Zhang_2020_CVPR,
author = {Zhang, Chen-Lin and Cao, Yun-Hao and Wu, Jianxin},
title = {Rethinking the Route Towards Weakly Supervised Object Localization},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Adversarial Feature Hallucination Networks for Few-Shot Learning-
[pdf]
[bibtex]@InProceedings{Li_2020_CVPR,
author = {Li, Kai and Zhang, Yulun and Li, Kunpeng and Fu, Yun},
title = {Adversarial Feature Hallucination Networks for Few-Shot Learning},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Conditional Gaussian Distribution Learning for Open Set Recognition-
[pdf]
[bibtex]@InProceedings{Sun_2020_CVPR,
author = {Sun, Xin and Yang, Zhenning and Zhang, Chi and Ling, Keck-Voon and Peng, Guohao},
title = {Conditional Gaussian Distribution Learning for Open Set Recognition},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Connect-and-Slice: An Hybrid Approach for Reconstructing 3D Objects-
[pdf]
[bibtex]@InProceedings{Fang_2020_CVPR,
author = {Fang, Hao and Lafarge, Florent},
title = {Connect-and-Slice: An Hybrid Approach for Reconstructing 3D Objects},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Attentive Weights Generation for Few Shot Learning via Information Maximization-
[pdf]
[bibtex]@InProceedings{Guo_2020_CVPR,
author = {Guo, Yiluan and Cheung, Ngai-Man},
title = {Attentive Weights Generation for Few Shot Learning via Information Maximization},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Assessing Eye Aesthetics for Automatic Multi-Reference Eye In-Painting-
[pdf]
[bibtex]@InProceedings{Yan_2020_CVPR,
author = {Yan, Bo and Lin, Qing and Tan, Weimin and Zhou, Shili},
title = {Assessing Eye Aesthetics for Automatic Multi-Reference Eye In-Painting},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
PuppeteerGAN: Arbitrary Portrait Animation With Semantic-Aware Appearance Transformation-
[pdf]
[bibtex]@InProceedings{Chen_2020_CVPR,
author = {Chen, Zhuo and Wang, Chaoyue and Yuan, Bo and Tao, Dacheng},
title = {PuppeteerGAN: Arbitrary Portrait Animation With Semantic-Aware Appearance Transformation},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
SEED: Semantics Enhanced Encoder-Decoder Framework for Scene Text Recognition-
[pdf]
[bibtex]@InProceedings{Qiao_2020_CVPR,
author = {Qiao, Zhi and Zhou, Yu and Yang, Dongbao and Zhou, Yucan and Wang, Weiping},
title = {SEED: Semantics Enhanced Encoder-Decoder Framework for Scene Text Recognition},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Texture and Shape Biased Two-Stream Networks for Clothing Classification and Attribute Recognition-
[pdf]
[bibtex]@InProceedings{Zhang_2020_CVPR,
author = {Zhang, Yuwei and Zhang, Peng and Yuan, Chun and Wang, Zhi},
title = {Texture and Shape Biased Two-Stream Networks for Clothing Classification and Attribute Recognition},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Distortion Agnostic Deep Watermarking-
[pdf]
[bibtex]@InProceedings{Luo_2020_CVPR,
author = {Luo, Xiyang and Zhan, Ruohan and Chang, Huiwen and Yang, Feng and Milanfar, Peyman},
title = {Distortion Agnostic Deep Watermarking},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
RMP-SNN: Residual Membrane Potential Neuron for Enabling Deeper High-Accuracy and Low-Latency Spiking Neural Network-
[pdf]
[bibtex]@InProceedings{Han_2020_CVPR,
author = {Han, Bing and Srinivasan, Gopalakrishnan and Roy, Kaushik},
title = {RMP-SNN: Residual Membrane Potential Neuron for Enabling Deeper High-Accuracy and Low-Latency Spiking Neural Network},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
BFBox: Searching Face-Appropriate Backbone and Feature Pyramid Network for Face Detector-
[pdf]
[bibtex]@InProceedings{Liu_2020_CVPR,
author = {Liu, Yang and Tang, Xu},
title = {BFBox: Searching Face-Appropriate Backbone and Feature Pyramid Network for Face Detector},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
PFCNN: Convolutional Neural Networks on 3D Surfaces Using Parallel Frames-
[pdf]
[bibtex]@InProceedings{Yang_2020_CVPR,
author = {Yang, Yuqi and Liu, Shilin and Pan, Hao and Liu, Yang and Tong, Xin},
title = {PFCNN: Convolutional Neural Networks on 3D Surfaces Using Parallel Frames},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
iTAML: An Incremental Task-Agnostic Meta-learning Approach-
[pdf]
[bibtex]@InProceedings{Rajasegaran_2020_CVPR,
author = {Rajasegaran, Jathushan and Khan, Salman and Hayat, Munawar and Khan, Fahad Shahbaz and Shah, Mubarak},
title = {iTAML: An Incremental Task-Agnostic Meta-learning Approach},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Optimal least-squares solution to the hand-eye calibration problem-
[pdf]
[bibtex]@InProceedings{Dekel_2020_CVPR,
author = {Dekel, Amit and Harenstam-Nielsen, Linus and Caccamo, Sergio},
title = {Optimal least-squares solution to the hand-eye calibration problem},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
MnasFPN: Learning Latency-Aware Pyramid Architecture for Object Detection on Mobile Devices-
[pdf]
[bibtex]@InProceedings{Chen_2020_CVPR,
author = {Chen, Bo and Ghiasi, Golnaz and Liu, Hanxiao and Lin, Tsung-Yi and Kalenichenko, Dmitry and Adam, Hartwig and Le, Quoc V.},
title = {MnasFPN: Learning Latency-Aware Pyramid Architecture for Object Detection on Mobile Devices},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
VSGNet: Spatial Attention Network for Detecting Human Object Interactions Using Graph Convolutions-
[pdf]
[bibtex]@InProceedings{Ulutan_2020_CVPR,
author = {Ulutan, Oytun and Iftekhar, A S M and Manjunath, B. S.},
title = {VSGNet: Spatial Attention Network for Detecting Human Object Interactions Using Graph Convolutions},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
End-to-End Camera Calibration for Broadcast Videos-
[pdf]
[bibtex]@InProceedings{Sha_2020_CVPR,
author = {Sha, Long and Hobbs, Jennifer and Felsen, Panna and Wei, Xinyu and Lucey, Patrick and Ganguly, Sujoy},
title = {End-to-End Camera Calibration for Broadcast Videos},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Regularizing CNN Transfer Learning With Randomised Regression-
[pdf]
[bibtex]@InProceedings{Zhong_2020_CVPR,
author = {Zhong, Yang and Maki, Atsuto},
title = {Regularizing CNN Transfer Learning With Randomised Regression},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
KeypointNet: A Large-Scale 3D Keypoint Dataset Aggregated From Numerous Human Annotations-
[pdf]
[bibtex]@InProceedings{You_2020_CVPR,
author = {You, Yang and Lou, Yujing and Li, Chengkun and Cheng, Zhoujun and Li, Liangwei and Ma, Lizhuang and Lu, Cewu and Wang, Weiming},
title = {KeypointNet: A Large-Scale 3D Keypoint Dataset Aggregated From Numerous Human Annotations},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Hierarchical Clustering With Hard-Batch Triplet Loss for Person Re-Identification-
[pdf]
[bibtex]@InProceedings{Zeng_2020_CVPR,
author = {Zeng, Kaiwei and Ning, Munan and Wang, Yaohua and Guo, Yang},
title = {Hierarchical Clustering With Hard-Batch Triplet Loss for Person Re-Identification},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Joint Semantic Segmentation and Boundary Detection Using Iterative Pyramid Contexts-
[pdf]
[bibtex]@InProceedings{Zhen_2020_CVPR,
author = {Zhen, Mingmin and Wang, Jinglu and Zhou, Lei and Li, Shiwei and Shen, Tianwei and Shang, Jiaxiang and Fang, Tian and Quan, Long},
title = {Joint Semantic Segmentation and Boundary Detection Using Iterative Pyramid Contexts},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Attention-Guided Hierarchical Structure Aggregation for Image Matting-
[pdf]
[bibtex]@InProceedings{Qiao_2020_CVPR,
author = {Qiao, Yu and Liu, Yuhao and Yang, Xin and Zhou, Dongsheng and Xu, Mingliang and Zhang, Qiang and Wei, Xiaopeng},
title = {Attention-Guided Hierarchical Structure Aggregation for Image Matting},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
MetaFuse: A Pre-trained Fusion Model for Human Pose Estimation-
[pdf]
[bibtex]@InProceedings{Xie_2020_CVPR,
author = {Xie, Rongchang and Wang, Chunyu and Wang, Yizhou},
title = {MetaFuse: A Pre-trained Fusion Model for Human Pose Estimation},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Prior Guided GAN Based Semantic Inpainting-
[pdf]
[bibtex]@InProceedings{Lahiri_2020_CVPR,
author = {Lahiri, Avisek and Jain, Arnav Kumar and Agrawal, Sanskar and Mitra, Pabitra and Biswas, Prabir Kumar},
title = {Prior Guided GAN Based Semantic Inpainting},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Weakly Supervised Semantic Point Cloud Segmentation: Towards 10x Fewer Labels-
[pdf]
[bibtex]@InProceedings{Xu_2020_CVPR,
author = {Xu, Xun and Lee, Gim Hee},
title = {Weakly Supervised Semantic Point Cloud Segmentation: Towards 10x Fewer Labels},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Physically Realizable Adversarial Examples for LiDAR Object Detection-
[pdf]
[bibtex]@InProceedings{Tu_2020_CVPR,
author = {Tu, James and Ren, Mengye and Manivasagam, Sivabalan and Liang, Ming and Yang, Bin and Du, Richard and Cheng, Frank and Urtasun, Raquel},
title = {Physically Realizable Adversarial Examples for LiDAR Object Detection},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Combating Noisy Labels by Agreement: A Joint Training Method with Co-Regularization-
[pdf]
[bibtex]@InProceedings{Wei_2020_CVPR,
author = {Wei, Hongxin and Feng, Lei and Chen, Xiangyu and An, Bo},
title = {Combating Noisy Labels by Agreement: A Joint Training Method with Co-Regularization},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Light-weight Calibrator: A Separable Component for Unsupervised Domain Adaptation-
[pdf]
[bibtex]@InProceedings{Ye_2020_CVPR,
author = {Ye, Shaokai and Wu, Kailu and Zhou, Mu and Yang, Yunfei and Tan, Sia Huat and Xu, Kaidi and Song, Jiebo and Bao, Chenglong and Ma, Kaisheng},
title = {Light-weight Calibrator: A Separable Component for Unsupervised Domain Adaptation},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Learn to Augment: Joint Data Augmentation and Network Optimization for Text Recognition-
[pdf]
[bibtex]@InProceedings{Luo_2020_CVPR,
author = {Luo, Canjie and Zhu, Yuanzhi and Jin, Lianwen and Wang, Yongpan},
title = {Learn to Augment: Joint Data Augmentation and Network Optimization for Text Recognition},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Learning Selective Self-Mutual Attention for RGB-D Saliency Detection-
[pdf]
[bibtex]@InProceedings{Liu_2020_CVPR,
author = {Liu, Nian and Zhang, Ni and Han, Junwei},
title = {Learning Selective Self-Mutual Attention for RGB-D Saliency Detection},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Cross-domain Object Detection through Coarse-to-Fine Feature Adaptation-
[pdf]
[bibtex]@InProceedings{Zheng_2020_CVPR,
author = {Zheng, Yangtao and Huang, Di and Liu, Songtao and Wang, Yunhong},
title = {Cross-domain Object Detection through Coarse-to-Fine Feature Adaptation},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Estimating Low-Rank Region Likelihood Maps-
[pdf]
[bibtex]@InProceedings{Csurka_2020_CVPR,
author = {Csurka, Gabriela and Kato, Zoltan and Juhasz, Andor and Humenberger, Martin},
title = {Estimating Low-Rank Region Likelihood Maps},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Neural Head Reenactment with Latent Pose Descriptors-
[pdf]
[bibtex]@InProceedings{Burkov_2020_CVPR,
author = {Burkov, Egor and Pasechnik, Igor and Grigorev, Artur and Lempitsky, Victor},
title = {Neural Head Reenactment with Latent Pose Descriptors},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Learning Individual Speaking Styles for Accurate Lip to Speech Synthesis-
[pdf]
[bibtex]@InProceedings{Prajwal_2020_CVPR,
author = {Prajwal, K R and Mukhopadhyay, Rudrabha and Namboodiri, Vinay P. and Jawahar, C.V.},
title = {Learning Individual Speaking Styles for Accurate Lip to Speech Synthesis},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Self-Supervised Learning of Video-Induced Visual Invariances-
[pdf]
[bibtex]@InProceedings{Tschannen_2020_CVPR,
author = {Tschannen, Michael and Djolonga, Josip and Ritter, Marvin and Mahendran, Aravindh and Houlsby, Neil and Gelly, Sylvain and Lucic, Mario},
title = {Self-Supervised Learning of Video-Induced Visual Invariances},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Two-Stage Peer-Regularized Feature Recombination for Arbitrary Image Style Transfer-
[pdf]
[bibtex]@InProceedings{Svoboda_2020_CVPR,
author = {Svoboda, Jan and Anoosheh, Asha and Osendorfer, Christian and Masci, Jonathan},
title = {Two-Stage Peer-Regularized Feature Recombination for Arbitrary Image Style Transfer},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
MINA: Convex Mixed-Integer Programming for Non-Rigid Shape Alignment-
[pdf]
[bibtex]@InProceedings{Bernard_2020_CVPR,
author = {Bernard, Florian and Suri, Zeeshan Khan and Theobalt, Christian},
title = {MINA: Convex Mixed-Integer Programming for Non-Rigid Shape Alignment},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Improving One-Shot NAS by Suppressing the Posterior Fading-
[pdf]
[bibtex]@InProceedings{Li_2020_CVPR,
author = {Li, Xiang and Lin, Chen and Li, Chuming and Sun, Ming and Wu, Wei and Yan, Junjie and Ouyang, Wanli},
title = {Improving One-Shot NAS by Suppressing the Posterior Fading},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Incremental Few-Shot Object Detection-
[pdf]
[bibtex]@InProceedings{Perez-Rua_2020_CVPR,
author = {Perez-Rua, Juan-Manuel and Zhu, Xiatian and Hospedales, Timothy M. and Xiang, Tao},
title = {Incremental Few-Shot Object Detection},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Synthetic Learning: Learn From Distributed Asynchronized Discriminator GAN Without Sharing Medical Image Data-
[pdf]
[bibtex]@InProceedings{Chang_2020_CVPR,
author = {Chang, Qi and Qu, Hui and Zhang, Yikai and Sabuncu, Mert and Chen, Chao and Zhang, Tong and Metaxas, Dimitris N.},
title = {Synthetic Learning: Learn From Distributed Asynchronized Discriminator GAN Without Sharing Medical Image Data},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Exploring Category-Agnostic Clusters for Open-Set Domain Adaptation-
[pdf]
[bibtex]@InProceedings{Pan_2020_CVPR,
author = {Pan, Yingwei and Yao, Ting and Li, Yehao and Ngo, Chong-Wah and Mei, Tao},
title = {Exploring Category-Agnostic Clusters for Open-Set Domain Adaptation},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Regularizing Class-Wise Predictions via Self-Knowledge Distillation-
[pdf]
[bibtex]@InProceedings{Yun_2020_CVPR,
author = {Yun, Sukmin and Park, Jongjin and Lee, Kimin and Shin, Jinwoo},
title = {Regularizing Class-Wise Predictions via Self-Knowledge Distillation},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Hierarchical Graph Attention Network for Visual Relationship Detection-
[pdf]
[bibtex]@InProceedings{Mi_2020_CVPR,
author = {Mi, Li and Chen, Zhenzhong},
title = {Hierarchical Graph Attention Network for Visual Relationship Detection},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
M2m: Imbalanced Classification via Major-to-Minor Translation-
[pdf]
[bibtex]@InProceedings{Kim_2020_CVPR,
author = {Kim, Jaehyung and Jeong, Jongheon and Shin, Jinwoo},
title = {M2m: Imbalanced Classification via Major-to-Minor Translation},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
CenterMask: Real-Time Anchor-Free Instance Segmentation-
[pdf]
[bibtex]@InProceedings{Lee_2020_CVPR,
author = {Lee, Youngwan and Park, Jongyoul},
title = {CenterMask: Real-Time Anchor-Free Instance Segmentation},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Multi-Path Learning for Object Pose Estimation Across Domains-
[pdf]
[bibtex]@InProceedings{Sundermeyer_2020_CVPR,
author = {Sundermeyer, Martin and Durner, Maximilian and Puang, En Yen and Marton, Zoltan-Csaba and Vaskevicius, Narunas and Arras, Kai O. and Triebel, Rudolph},
title = {Multi-Path Learning for Object Pose Estimation Across Domains},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Incremental Learning in Online Scenario-
[pdf]
[bibtex]@InProceedings{He_2020_CVPR,
author = {He, Jiangpeng and Mao, Runyu and Shao, Zeman and Zhu, Fengqing},
title = {Incremental Learning in Online Scenario},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Enhanced Transport Distance for Unsupervised Domain Adaptation-
[pdf]
[bibtex]@InProceedings{Li_2020_CVPR,
author = {Li, Mengxue and Zhai, Yi-Ming and Luo, You-Wei and Ge, Peng-Fei and Ren, Chuan-Xian},
title = {Enhanced Transport Distance for Unsupervised Domain Adaptation},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
TESA: Tensor Element Self-Attention via Matricization-
[pdf]
[bibtex]@InProceedings{Babiloni_2020_CVPR,
author = {Babiloni, Francesca and Marras, Ioannis and Slabaugh, Gregory and Zafeiriou, Stefanos},
title = {TESA: Tensor Element Self-Attention via Matricization},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Training a Steerable CNN for Guidewire Detection-
[pdf]
[bibtex]@InProceedings{Li_2020_CVPR,
author = {Li, Donghang and Barbu, Adrian},
title = {Training a Steerable CNN for Guidewire Detection},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Superpixel Segmentation With Fully Convolutional Networks-
[pdf]
[bibtex]@InProceedings{Yang_2020_CVPR,
author = {Yang, Fengting and Sun, Qian and Jin, Hailin and Zhou, Zihan},
title = {Superpixel Segmentation With Fully Convolutional Networks},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
SharinGAN: Combining Synthetic and Real Data for Unsupervised Geometry Estimation-
[pdf]
[bibtex]@InProceedings{PNVR_2020_CVPR,
author = {PNVR, Koutilya and Zhou, Hao and Jacobs, David},
title = {SharinGAN: Combining Synthetic and Real Data for Unsupervised Geometry Estimation},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Label Distribution Learning on Auxiliary Label Space Graphs for Facial Expression Recognition-
[pdf]
[bibtex]@InProceedings{Chen_2020_CVPR,
author = {Chen, Shikai and Wang, Jianfeng and Chen, Yuedong and Shi, Zhongchao and Geng, Xin and Rui, Yong},
title = {Label Distribution Learning on Auxiliary Label Space Graphs for Facial Expression Recognition},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Deep Residual Flow for Out of Distribution Detection-
[pdf]
[bibtex]@InProceedings{Zisselman_2020_CVPR,
author = {Zisselman, Ev and Tamar, Aviv},
title = {Deep Residual Flow for Out of Distribution Detection},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
FeatureFlow: Robust Video Interpolation via Structure-to-Texture Generation-
[pdf]
[bibtex]@InProceedings{Gui_2020_CVPR,
author = {Gui, Shurui and Wang, Chaoyue and Chen, Qihua and Tao, Dacheng},
title = {FeatureFlow: Robust Video Interpolation via Structure-to-Texture Generation},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Learning Nanoscale Motion Patterns of Vesicles in Living Cells-
[pdf]
[bibtex]@InProceedings{Sekh_2020_CVPR,
author = {Sekh, Arif Ahmed and Opstad, Ida Sundvor and Birgisdottir, Asa Birna and Myrmel, Truls and Ahluwalia, Balpreet Singh and Agarwal, Krishna and Prasad, Dilip K.},
title = {Learning Nanoscale Motion Patterns of Vesicles in Living Cells},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Improving Action Segmentation via Graph-Based Temporal Reasoning-
[pdf]
[bibtex]@InProceedings{Huang_2020_CVPR,
author = {Huang, Yifei and Sugano, Yusuke and Sato, Yoichi},
title = {Improving Action Segmentation via Graph-Based Temporal Reasoning},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Episode-Based Prototype Generating Network for Zero-Shot Learning-
[pdf]
[bibtex]@InProceedings{Yu_2020_CVPR,
author = {Yu, Yunlong and Ji, Zhong and Han, Jungong and Zhang, Zhongfei},
title = {Episode-Based Prototype Generating Network for Zero-Shot Learning},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Learning to Segment the Tail-
[pdf]
[bibtex]@InProceedings{Hu_2020_CVPR,
author = {Hu, Xinting and Jiang, Yi and Tang, Kaihua and Chen, Jingyuan and Miao, Chunyan and Zhang, Hanwang},
title = {Learning to Segment the Tail},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Learning to Evaluate Perception Models Using Planner-Centric Metrics-
[pdf]
[bibtex]@InProceedings{Philion_2020_CVPR,
author = {Philion, Jonah and Kar, Amlan and Fidler, Sanja},
title = {Learning to Evaluate Perception Models Using Planner-Centric Metrics},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Where, What, Whether: Multi-Modal Learning Meets Pedestrian Detection-
[pdf]
[bibtex]@InProceedings{Luo_2020_CVPR,
author = {Luo, Yan and Zhang, Chongyang and Zhao, Muming and Zhou, Hao and Sun, Jun},
title = {Where, What, Whether: Multi-Modal Learning Meets Pedestrian Detection},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
CoverNet: Multimodal Behavior Prediction Using Trajectory Sets-
[pdf]
[bibtex]@InProceedings{Phan-Minh_2020_CVPR,
author = {Phan-Minh, Tung and Grigore, Elena Corina and Boulton, Freddy A. and Beijbom, Oscar and Wolff, Eric M.},
title = {CoverNet: Multimodal Behavior Prediction Using Trajectory Sets},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Real-World Person Re-Identification via Degradation Invariance Learning-
[pdf]
[bibtex]@InProceedings{Huang_2020_CVPR,
author = {Huang, Yukun and Zha, Zheng-Jun and Fu, Xueyang and Hong, Richang and Li, Liang},
title = {Real-World Person Re-Identification via Degradation Invariance Learning},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Defending and Harnessing the Bit-Flip Based Adversarial Weight Attack-
[pdf]
[bibtex]@InProceedings{He_2020_CVPR,
author = {He, Zhezhi and Rakin, Adnan Siraj and Li, Jingtao and Chakrabarti, Chaitali and Fan, Deliang},
title = {Defending and Harnessing the Bit-Flip Based Adversarial Weight Attack},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Adversarial Latent Autoencoders-
[pdf]
[bibtex]@InProceedings{Pidhorskyi_2020_CVPR,
author = {Pidhorskyi, Stanislav and Adjeroh, Donald A. and Doretto, Gianfranco},
title = {Adversarial Latent Autoencoders},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Adaptive Fractional Dilated Convolution Network for Image Aesthetics Assessment-
[pdf]
[bibtex]@InProceedings{Chen_2020_CVPR,
author = {Chen, Qiuyu and Zhang, Wei and Zhou, Ning and Lei, Peng and Xu, Yi and Zheng, Yu and Fan, Jianping},
title = {Adaptive Fractional Dilated Convolution Network for Image Aesthetics Assessment},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Deep Generative Model for Robust Imbalance Classification-
[pdf]
[bibtex]@InProceedings{Wang_2020_CVPR,
author = {Wang, Xinyue and Lyu, Yilin and Jing, Liping},
title = {Deep Generative Model for Robust Imbalance Classification},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Learning Deep Network for Detecting 3D Object Keypoints and 6D Poses-
[pdf]
[bibtex]@InProceedings{Zhao_2020_CVPR,
author = {Zhao, Wanqing and Zhang, Shaobo and Guan, Ziyu and Zhao, Wei and Peng, Jinye and Fan, Jianping},
title = {Learning Deep Network for Detecting 3D Object Keypoints and 6D Poses},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
MetaIQA: Deep Meta-Learning for No-Reference Image Quality Assessment-
[pdf]
[bibtex]@InProceedings{Zhu_2020_CVPR,
author = {Zhu, Hancheng and Li, Leida and Wu, Jinjian and Dong, Weisheng and Shi, Guangming},
title = {MetaIQA: Deep Meta-Learning for No-Reference Image Quality Assessment},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Sketchformer: Transformer-Based Representation for Sketched Structure-
[pdf]
[bibtex]@InProceedings{Ribeiro_2020_CVPR,
author = {Ribeiro, Leo Sampaio Ferraz and Bui, Tu and Collomosse, John and Ponti, Moacir},
title = {Sketchformer: Transformer-Based Representation for Sketched Structure},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Cylindrical Convolutional Networks for Joint Object Detection and Viewpoint Estimation-
[pdf]
[bibtex]@InProceedings{Joung_2020_CVPR,
author = {Joung, Sunghun and Kim, Seungryong and Kim, Hanjae and Kim, Minsu and Kim, Ig-Jae and Cho, Junghyun and Sohn, Kwanghoon},
title = {Cylindrical Convolutional Networks for Joint Object Detection and Viewpoint Estimation},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Learning a Unified Sample Weighting Network for Object Detection-
[pdf]
[bibtex]@InProceedings{Cai_2020_CVPR,
author = {Cai, Qi and Pan, Yingwei and Wang, Yu and Liu, Jingen and Yao, Ting and Mei, Tao},
title = {Learning a Unified Sample Weighting Network for Object Detection},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Old Is Gold: Redefining the Adversarially Learned One-Class Classifier Training Paradigm-
[pdf]
[bibtex]@InProceedings{Zaheer_2020_CVPR,
author = {Zaheer, Muhammad Zaigham and Lee, Jin-Ha and Astrid, Marcella and Lee, Seung-Ik},
title = {Old Is Gold: Redefining the Adversarially Learned One-Class Classifier Training Paradigm},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
An Adaptive Neural Network for Unsupervised Mosaic Consistency Analysis in Image Forensics-
[pdf]
[bibtex]@InProceedings{Bammey_2020_CVPR,
author = {Bammey, Quentin and Gioi, Rafael Grompone von and Morel, Jean-Michel},
title = {An Adaptive Neural Network for Unsupervised Mosaic Consistency Analysis in Image Forensics},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
McFlow: Monte Carlo Flow Models for Data Imputation-
[pdf]
[bibtex]@InProceedings{Richardson_2020_CVPR,
author = {Richardson, Trevor W. and Wu, Wencheng and Lin, Lei and Xu, Beilei and Bernal, Edgar A.},
title = {McFlow: Monte Carlo Flow Models for Data Imputation},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Learning to See Through Obstructions-
[pdf]
[bibtex]@InProceedings{Liu_2020_CVPR,
author = {Liu, Yu-Lun and Lai, Wei-Sheng and Yang, Ming-Hsuan and Chuang, Yung-Yu and Huang, Jia-Bin},
title = {Learning to See Through Obstructions},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
GaitPart: Temporal Part-Based Model for Gait Recognition-
[pdf]
[bibtex]@InProceedings{Fan_2020_CVPR,
author = {Fan, Chao and Peng, Yunjie and Cao, Chunshui and Liu, Xu and Hou, Saihui and Chi, Jiannan and Huang, Yongzhen and Li, Qing and He, Zhiqiang},
title = {GaitPart: Temporal Part-Based Model for Gait Recognition},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
EmotiCon: Context-Aware Multimodal Emotion Recognition Using Frege's Principle-
[pdf]
[bibtex]@InProceedings{Mittal_2020_CVPR,
author = {Mittal, Trisha and Guhan, Pooja and Bhattacharya, Uttaran and Chandra, Rohan and Bera, Aniket and Manocha, Dinesh},
title = {EmotiCon: Context-Aware Multimodal Emotion Recognition Using Frege's Principle},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Can Deep Learning Recognize Subtle Human Activities?-
[pdf]
[bibtex]@InProceedings{Jacquot_2020_CVPR,
author = {Jacquot, Vincent and Ying, Zhuofan and Kreiman, Gabriel},
title = {Can Deep Learning Recognize Subtle Human Activities?},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
PhysGAN: Generating Physical-World-Resilient Adversarial Examples for Autonomous Driving-
[pdf]
[bibtex]@InProceedings{Kong_2020_CVPR,
author = {Kong, Zelun and Guo, Junfeng and Li, Ang and Liu, Cong},
title = {PhysGAN: Generating Physical-World-Resilient Adversarial Examples for Autonomous Driving},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
ILFO: Adversarial Attack on Adaptive Neural Networks-
[pdf]
[bibtex]@InProceedings{Haque_2020_CVPR,
author = {Haque, Mirazul and Chauhan, Anki and Liu, Cong and Yang, Wei},
title = {ILFO: Adversarial Attack on Adaptive Neural Networks},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
On Translation Invariance in CNNs: Convolutional Layers Can Exploit Absolute Spatial Location-
[pdf]
[bibtex]@InProceedings{Kayhan_2020_CVPR,
author = {Kayhan, Osman Semih and Gemert, Jan C. van},
title = {On Translation Invariance in CNNs: Convolutional Layers Can Exploit Absolute Spatial Location},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Diverse Image Generation via Self-Conditioned GANs-
[pdf]
[bibtex]@InProceedings{Liu_2020_CVPR,
author = {Liu, Steven and Wang, Tongzhou and Bau, David and Zhu, Jun-Yan and Torralba, Antonio},
title = {Diverse Image Generation via Self-Conditioned GANs},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Inducing Hierarchical Compositional Model by Sparsifying Generator Network-
[pdf]
[bibtex]@InProceedings{Xing_2020_CVPR,
author = {Xing, Xianglei and Wu, Tianfu and Zhu, Song-Chun and Wu, Ying Nian},
title = {Inducing Hierarchical Compositional Model by Sparsifying Generator Network},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
CARP: Compression Through Adaptive Recursive Partitioning for Multi-Dimensional Images-
[pdf]
[bibtex]@InProceedings{Liu_2020_CVPR,
author = {Liu, Rongjie and Li, Meng and Ma, Li},
title = {CARP: Compression Through Adaptive Recursive Partitioning for Multi-Dimensional Images},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
GrappaNet: Combining Parallel Imaging With Deep Learning for Multi-Coil MRI Reconstruction-
[pdf]
[bibtex]@InProceedings{Sriram_2020_CVPR,
author = {Sriram, Anuroop and Zbontar, Jure and Murrell, Tullie and Zitnick, C. Lawrence and Defazio, Aaron and Sodickson, Daniel K.},
title = {GrappaNet: Combining Parallel Imaging With Deep Learning for Multi-Coil MRI Reconstruction},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Can Weight Sharing Outperform Random Architecture Search? An Investigation With TuNAS-
[pdf]
[bibtex]@InProceedings{Bender_2020_CVPR,
author = {Bender, Gabriel and Liu, Hanxiao and Chen, Bo and Chu, Grace and Cheng, Shuyang and Kindermans, Pieter-Jan and Le, Quoc V.},
title = {Can Weight Sharing Outperform Random Architecture Search? An Investigation With TuNAS},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Context Aware Graph Convolution for Skeleton-Based Action Recognition-
[pdf]
[bibtex]@InProceedings{Zhang_2020_CVPR,
author = {Zhang, Xikun and Xu, Chang and Tao, Dacheng},
title = {Context Aware Graph Convolution for Skeleton-Based Action Recognition},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Fast(er) Reconstruction of Shredded Text Documents via Self-Supervised Deep Asymmetric Metric Learning-
[pdf]
[bibtex]@InProceedings{Paixao_2020_CVPR,
author = {Paixao, Thiago M. and Berriel, Rodrigo F. and Boeres, Maria C. S. and Koerich, Alessandro L. and Badue, Claudine and Souza, Alberto F. De and Oliveira-Santos, Thiago},
title = {Fast(er) Reconstruction of Shredded Text Documents via Self-Supervised Deep Asymmetric Metric Learning},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Revisiting Pose-Normalization for Fine-Grained Few-Shot Recognition-
[pdf]
[bibtex]@InProceedings{Tang_2020_CVPR,
author = {Tang, Luming and Wertheimer, Davis and Hariharan, Bharath},
title = {Revisiting Pose-Normalization for Fine-Grained Few-Shot Recognition},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
RankMI: A Mutual Information Maximizing Ranking Loss-
[pdf]
[bibtex]@InProceedings{Kemertas_2020_CVPR,
author = {Kemertas, Mete and Pishdad, Leila and Derpanis, Konstantinos G. and Fazly, Afsaneh},
title = {RankMI: A Mutual Information Maximizing Ranking Loss},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Learning Memory-Guided Normality for Anomaly Detection-
[pdf]
[bibtex]@InProceedings{Park_2020_CVPR,
author = {Park, Hyunjong and Noh, Jongyoun and Ham, Bumsub},
title = {Learning Memory-Guided Normality for Anomaly Detection},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Appearance Shock Grammar for Fast Medial Axis Extraction From Real Images-
[pdf]
[bibtex]@InProceedings{Camaro_2020_CVPR,
author = {Camaro, Charles-Olivier Dufresne and Rezanejad, Morteza and Tsogkas, Stavros and Siddiqi, Kaleem and Dickinson, Sven},
title = {Appearance Shock Grammar for Fast Medial Axis Extraction From Real Images},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Generalizing Hand Segmentation in Egocentric Videos With Uncertainty-Guided Model Adaptation-
[pdf]
[bibtex]@InProceedings{Cai_2020_CVPR,
author = {Cai, Minjie and Lu, Feng and Sato, Yoichi},
title = {Generalizing Hand Segmentation in Egocentric Videos With Uncertainty-Guided Model Adaptation},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
DeFeat-Net: General Monocular Depth via Simultaneous Unsupervised Representation Learning-
[pdf]
[bibtex]@InProceedings{Spencer_2020_CVPR,
author = {Spencer, Jaime and Bowden, Richard and Hadfield, Simon},
title = {DeFeat-Net: General Monocular Depth via Simultaneous Unsupervised Representation Learning},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Learning Visual Motion Segmentation Using Event Surfaces-
[pdf]
[bibtex]@InProceedings{Mitrokhin_2020_CVPR,
author = {Mitrokhin, Anton and Hua, Zhiyuan and Fermuller, Cornelia and Aloimonos, Yiannis},
title = {Learning Visual Motion Segmentation Using Event Surfaces},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Social-STGCNN: A Social Spatio-Temporal Graph Convolutional Neural Network for Human Trajectory Prediction-
[pdf]
[bibtex]@InProceedings{Mohamed_2020_CVPR,
author = {Mohamed, Abduallah and Qian, Kun and Elhoseiny, Mohamed and Claudel, Christian},
title = {Social-STGCNN: A Social Spatio-Temporal Graph Convolutional Neural Network for Human Trajectory Prediction},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Discriminative Multi-Modality Speech Recognition-
[pdf]
[bibtex]@InProceedings{Xu_2020_CVPR,
author = {Xu, Bo and Lu, Cheng and Guo, Yandong and Wang, Jacob},
title = {Discriminative Multi-Modality Speech Recognition},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Clean-Label Backdoor Attacks on Video Recognition Models-
[pdf]
[bibtex]@InProceedings{Zhao_2020_CVPR,
author = {Zhao, Shihao and Ma, Xingjun and Zheng, Xiang and Bailey, James and Chen, Jingjing and Jiang, Yu-Gang},
title = {Clean-Label Backdoor Attacks on Video Recognition Models},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Detecting Adversarial Samples Using Influence Functions and Nearest Neighbors-
[pdf]
[bibtex]@InProceedings{Cohen_2020_CVPR,
author = {Cohen, Gilad and Sapiro, Guillermo and Giryes, Raja},
title = {Detecting Adversarial Samples Using Influence Functions and Nearest Neighbors},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Unsupervised Model Personalization While Preserving Privacy and Scalability: An Open Problem-
[pdf]
[bibtex]@InProceedings{Lange_2020_CVPR,
author = {Lange, Matthias De and Jia, Xu and Parisot, Sarah and Leonardis, Ales and Slabaugh, Gregory and Tuytelaars, Tinne},
title = {Unsupervised Model Personalization While Preserving Privacy and Scalability: An Open Problem},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
GIFnets: Differentiable GIF Encoding Framework-
[pdf]
[bibtex]@InProceedings{Yoo_2020_CVPR,
author = {Yoo, Innfarn and Luo, Xiyang and Wang, Yilin and Yang, Feng and Milanfar, Peyman},
title = {GIFnets: Differentiable GIF Encoding Framework},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Learning Invariant Representation for Unsupervised Image Restoration-
[pdf]
[bibtex]@InProceedings{Du_2020_CVPR,
author = {Du, Wenchao and Chen, Hu and Yang, Hongyu},
title = {Learning Invariant Representation for Unsupervised Image Restoration},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Improved Few-Shot Visual Classification-
[pdf]
[bibtex]@InProceedings{Bateni_2020_CVPR,
author = {Bateni, Peyman and Goyal, Raghav and Masrani, Vaden and Wood, Frank and Sigal, Leonid},
title = {Improved Few-Shot Visual Classification},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Learning Weighted Submanifolds With Variational Autoencoders and Riemannian Variational Autoencoders-
[pdf]
[bibtex]@InProceedings{Miolane_2020_CVPR,
author = {Miolane, Nina and Holmes, Susan},
title = {Learning Weighted Submanifolds With Variational Autoencoders and Riemannian Variational Autoencoders},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Learning Geocentric Object Pose in Oblique Monocular Images-
[pdf]
[bibtex]@InProceedings{Christie_2020_CVPR,
author = {Christie, Gordon and Abujder, Rodrigo Rene Rai Munoz and Foster, Kevin and Hagstrom, Shea and Hager, Gregory D. and Brown, Myron Z.},
title = {Learning Geocentric Object Pose in Oblique Monocular Images},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Understanding Adversarial Examples From the Mutual Influence of Images and Perturbations-
[pdf]
[bibtex]@InProceedings{Zhang_2020_CVPR,
author = {Zhang, Chaoning and Benz, Philipp and Imtiaz, Tooba and Kweon, In So},
title = {Understanding Adversarial Examples From the Mutual Influence of Images and Perturbations},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Your Local GAN: Designing Two Dimensional Local Attention Mechanisms for Generative Models-
[pdf]
[bibtex]@InProceedings{Daras_2020_CVPR,
author = {Daras, Giannis and Odena, Augustus and Zhang, Han and Dimakis, Alexandros G.},
title = {Your Local GAN: Designing Two Dimensional Local Attention Mechanisms for Generative Models},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
MoreFusion: Multi-object Reasoning for 6D Pose Estimation from Volumetric Fusion-
[pdf]
[bibtex]@InProceedings{Wada_2020_CVPR,
author = {Wada, Kentaro and Sucar, Edgar and James, Stephen and Lenton, Daniel and Davison, Andrew J.},
title = {MoreFusion: Multi-object Reasoning for 6D Pose Estimation from Volumetric Fusion},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
HCNAF: Hyper-Conditioned Neural Autoregressive Flow and its Application for Probabilistic Occupancy Map Forecasting-
[pdf]
[bibtex]@InProceedings{Oh_2020_CVPR,
author = {Oh, Geunseob and Valois, Jean-Sebastien},
title = {HCNAF: Hyper-Conditioned Neural Autoregressive Flow and its Application for Probabilistic Occupancy Map Forecasting},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Detail-recovery Image Deraining via Context Aggregation Networks-
[pdf]
[bibtex]@InProceedings{Deng_2020_CVPR,
author = {Deng, Sen and Wei, Mingqiang and Wang, Jun and Feng, Yidan and Liang, Luming and Xie, Haoran and Wang, Fu Lee and Wang, Meng},
title = {Detail-recovery Image Deraining via Context Aggregation Networks},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
MCEN: Bridging Cross-Modal Gap between Cooking Recipes and Dish Images with Latent Variable Model-
[pdf]
[bibtex]@InProceedings{Fu_2020_CVPR,
author = {Fu, Han and Wu, Rui and Liu, Chenghao and Sun, Jianling},
title = {MCEN: Bridging Cross-Modal Gap between Cooking Recipes and Dish Images with Latent Variable Model},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Hypergraph Attention Networks for Multimodal Learning-
[pdf]
[bibtex]@InProceedings{Kim_2020_CVPR,
author = {Kim, Eun-Sol and Kang, Woo Young and On, Kyoung-Woon and Heo, Yu-Jung and Zhang, Byoung-Tak},
title = {Hypergraph Attention Networks for Multimodal Learning},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Moving in the Right Direction: A Regularization for Deep Metric Learning-
[pdf]
[bibtex]@InProceedings{Mohan_2020_CVPR,
author = {Mohan, Deen Dayal and Sankaran, Nishant and Fedorishin, Dennis and Setlur, Srirangaraj and Govindaraju, Venu},
title = {Moving in the Right Direction: A Regularization for Deep Metric Learning},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Rethinking Depthwise Separable Convolutions: How Intra-Kernel Correlations Lead to Improved MobileNets-
[pdf]
[bibtex]@InProceedings{Haase_2020_CVPR,
author = {Haase, Daniel and Amthor, Manuel},
title = {Rethinking Depthwise Separable Convolutions: How Intra-Kernel Correlations Lead to Improved MobileNets},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Seeing without Looking: Contextual Rescoring of Object Detections for AP Maximization-
[pdf]
[bibtex]@InProceedings{Pato_2020_CVPR,
author = {Pato, Lourenco V. and Negrinho, Renato and Aguiar, Pedro M. Q.},
title = {Seeing without Looking: Contextual Rescoring of Object Detections for AP Maximization},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
End-to-End Adversarial-Attention Network for Multi-Modal Clustering-
[pdf]
[bibtex]@InProceedings{Zhou_2020_CVPR,
author = {Zhou, Runwu and Shen, Yi-Dong},
title = {End-to-End Adversarial-Attention Network for Multi-Modal Clustering},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Fast Sparse ConvNets-
[pdf]
[bibtex]@InProceedings{Elsen_2020_CVPR,
author = {Elsen, Erich and Dukhan, Marat and Gale, Trevor and Simonyan, Karen},
title = {Fast Sparse ConvNets},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Few Sample Knowledge Distillation for Efficient Network Compression-
[pdf]
[bibtex]@InProceedings{Li_2020_CVPR,
author = {Li, Tianhong and Li, Jianguo and Liu, Zhuang and Zhang, Changshui},
title = {Few Sample Knowledge Distillation for Efficient Network Compression},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Predicting Sharp and Accurate Occlusion Boundaries in Monocular Depth Estimation Using Displacement Fields-
[pdf]
[bibtex]@InProceedings{Ramamonjisoa_2020_CVPR,
author = {Ramamonjisoa, Michael and Du, Yuming and Lepetit, Vincent},
title = {Predicting Sharp and Accurate Occlusion Boundaries in Monocular Depth Estimation Using Displacement Fields},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Shape correspondence using anisotropic Chebyshev spectral CNNs-
[pdf]
[bibtex]@InProceedings{Li_2020_CVPR,
author = {Li, Qinsong and Liu, Shengjun and Hu, Ling and Liu, Xinru},
title = {Shape correspondence using anisotropic Chebyshev spectral CNNs},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
RetinaTrack: Online Single Stage Joint Detection and Tracking-
[pdf]
[bibtex]@InProceedings{Lu_2020_CVPR,
author = {Lu, Zhichao and Rathod, Vivek and Votel, Ronny and Huang, Jonathan},
title = {RetinaTrack: Online Single Stage Joint Detection and Tracking},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
Multimodal Categorization of Crisis Events in Social Media-
[pdf]
[bibtex]@InProceedings{Abavisani_2020_CVPR,
author = {Abavisani, Mahdi and Wu, Liwei and Hu, Shengli and Tetreault, Joel and Jaimes, Alejandro},
title = {Multimodal Categorization of Crisis Events in Social Media},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
SPARE3D: A Dataset for SPAtial REasoning on Three-View Line Drawings-
[pdf]
[bibtex]@InProceedings{Han_2020_CVPR,
author = {Han, Wenyu and Xiang, Siyuan and Liu, Chenhui and Wang, Ruoyu and Feng, Chen},
title = {SPARE3D: A Dataset for SPAtial REasoning on Three-View Line Drawings},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
SwapText: Image Based Texts Transfer in Scenes-
[pdf]
[bibtex]@InProceedings{Yang_2020_CVPR,
author = {Yang, Qiangpeng and Huang, Jun and Lin, Wei},
title = {SwapText: Image Based Texts Transfer in Scenes},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
OrigamiNet: Weakly-Supervised, Segmentation-Free, One-Step, Full Page Text Recognition by learning to unfold-
[pdf]
[bibtex]@InProceedings{Yousef_2020_CVPR,
author = {Yousef, Mohamed and Bishop, Tom E.},
title = {OrigamiNet: Weakly-Supervised, Segmentation-Free, One-Step, Full Page Text Recognition by learning to unfold},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
FroDO: From Detections to 3D Objects-
[pdf]
[bibtex]@InProceedings{Runz_2020_CVPR,
author = {Runz, Martin and Li, Kejie and Tang, Meng and Ma, Lingni and Kong, Chen and Schmidt, Tanner and Reid, Ian and Agapito, Lourdes and Straub, Julian and Lovegrove, Steven and Newcombe, Richard},
title = {FroDO: From Detections to 3D Objects},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}


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The variability of an expression governs the degree of freedom with which the expression may vary during simulation. Variability is a specific property but has clear connections with the notion of data type. The example classes below illustrates the subtyping and variability rules for declaration equations and normal equations.
This is not allowed, since p1 + 2 is not a constant expression
Below the error message is shown, after trying to simulate the Constants model.
This is correct, since p1 + 2 has the same variability as p1.
The equation in TestEquations is not correct, since b is a discrete time and noEvent(x > 1) is a continuous time expression.
Below the error message is shown, after trying to simulate the TestEquations model.


SmartGreenHouse
A Project for the Course Embedded Systems by Michael Schäfer
Tools to create the Website :
-
Bootstrap v4
- jQuery
- Font Awesome
- Github
The SmartGreenHouse is a greenhouse which can hold up to two plants. It automatically checks certain measurement values of inside the greenhouse to enable the best possible circumstances for the chosen plants to grow


--- layout: default title: Projects ---
Fremont Border has been lost for some time. His girlfriend has become distant, his family apathetic; his best friend hasn’t changed at all. To cope, he’s relied on drink, drugs, and lucid dreaming. He wants to escape London. He wants to go and sell mangoes on a beach.
One chilly morning he wakes at a bus stop, groggy and hungover, to find a note on his lap. He follows the instructions of the note, which leads him to meet Orla: an urban nomad with a mysterious past. Through this chance encounter, Fremont becomes exposed to a new way of living. Curiosity, beauty, and adventure abound, though it’s clear there’s something she’s not telling him.
When Orla’s secrets begin to mount and his best friend sinks into a world of trouble, Fremont finds he is more alone than ever.
Should he stay in London with those he loves, even if it means living with disillusion and regret? Or should he take after Orla and pursue a life that may yet save his soul?
Afghanistan's Wakhan Corridor is the gateway to the Little Pamir: one of the most remote inhabited places in the world. Sandwiched between China, Pakistan and Tajikistan at over 4,000 metres, the Little Pamir is home to Kyrgyz nomad settlements and the stunning Lake Chaqmaqtin. It is also about to change forever, as Chinese authorities begin work on a highway that will bring the valley hurtling into the 21st century.
Olly Lawson’s firsthand account—written in diary form—sheds light on a region rarely explored by Westerners. When he is let go from his job as a travel agent the day before departure, he suddenly finds the trip assuming an importance beyond mere adventure. Accompanied by two former colleagues, the trip sees them endure a grueling ten-day hike, nail-biting car journeys and an assortment of memorable characters.
With soaring descriptions of the landscape and snippets of philosophical musings, these travel notes will take you from leafy London to the Roof of the World in no time.
An ambitious director will leave no stone unturned in her production of a fiendishly difficult and disturbing
play. The Maiden's Toy features a fast-moving account of the weeks leading up to the unveiling of her new production
and focuses on the director's increasingly twisted relationship with her young leading male. New writing exploring the pursuit
of perfection and the boundaries that must be crossed to acheive it.
Performed at the Edinburgh Fringe Festival


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You have successfully logged out from the Spring Cloud Data Flow Dashboard.
Please keep in mind that you are most likely still logged in with your oauth
provider. Therefore, going to the main Dashboard URL will log you back in,
unless you also log out from your oauth provider.


 Some people love both animals. But if you had to live with only one, which would you choose?
From my perspective, I prefer Dogs, but that's not mean i hate Cats. Let's
Let me introduce you some reasons why i think Dogs are better than Cats
It's not in a cat's nature to defend you or your home. Cats are more likely to run and hide when faced with trouble.
On the other hand, most dogs will instinctively protect their owners and their territory. They'll bark or growl to alert you to the presence of strangers, and many will even scare off intruders. Dogs can sense our fear and they'll respond if they think we feel threatened.
If you try to control a cat and you might hear the tiny sound of kitty laughter. Most cats will go where they want to go, jump where they want to jump, scratch where they want to scratch, and mark whatever they think needs marking. Then there are those hairballs, which are most easily found when you're barefoot in the middle of the night.
You can usually crate train a dog and keep him and your home safe and secure while you're away. Most crate-trained dogs consider their crates to be their own special places.
Dogs have been domesticated for 15,000 to 35,000 years or more. Dogs have been the faithful companions and loyal helpers of the human race throughout history.
Cats seem to know that they were once worshiped as gods. Perhaps they resent the fact those days have ended. They may still be holding it against us.
Cats are complicated. Dogs are not. A dog will love you every minute of every day. Scientists at Emory University conducted a study that proved it, too. Using MRI technology, they were able to show the reward center of doggy brains lit up like fireworks when they smelled their owner’s scent.
Science studies many things most people may deem pointless. Not the study of cats, however. Owning a cat has lead to lower stress-levels, which in turn lowers your risk of heart disease. Not only that, but children raised in the presence of cats (kids at <1 year or thereabouts) have higher chances of immunity to many common allergies, aside from just general pet alergies. Furthermore, while not beneficial from a health point of view, a study was conducted that showed that 90% of women believe that men with cats are nicer and more caring than those without.
Whether any of that science mumbo-jumbo has any standing in reality, I personally have no idea. What I do know is that Dr. Seuss created a character by the name of Cat in the Hat. Did he create a character called "Dog in the Hat"? No he did not.
Perhaps you need further convincing? Look no further than the table below.
I believe I rest my case.
~written by Andrew


Linux Huge Page
by Wenwei Weng
When a process uses some memory, the CPU is marking the RAM as used by that process. For efficiency, the CPU allocate RAM by chunks of 4K bytes (it’s the default value on many platforms). Those chunks are named pages. Those pages can be swapped to disk, etc.
Since the process address space are virtual in Linux, the CPU and the operating system have to remember which page belong to which process, and where it is stored, i.e. translate from virtual to physical address. The translation is done through TLB. A TLB is a cache of virtual-to-physical translations. Typically this is a very scarce resource on processor. Operating systems try to make best use of limited number of TLB resources. Huge page is a way to reduce number of pages in the kernel so that less TLB entries are used, translation will be faster.
#How to check if the running kernel supports huge page ?
By checking the kernel config, we can find if huge pages is supported.
#How to check what are supported huge page size using “hugeadm” tool?
The above output shows that the supported huge page size is 2MB.
#How to check the current huge pages status?
where: HugePages_Total is the size of the pool of huge pages. HugePages_Free is the number of huge pages in the pool that are not yet allocated. HugePages_Rsvd is short for “reserved,” and is the number of huge pages for which a commitment to allocate from the pool has been made, but no allocation has yet been made. Reserved huge pages guarantee that an application will be able to allocate a huge page from the pool of huge pages at fault time. HugePages_Surp is short for “surplus,” and is the number of huge pages in the pool above the value in /proc/sys/vm/nr_hugepages. The maximum number of surplus huge pages is controlled by /proc/sys/vm/nr_overcommit_hugepages.
The above output says there is no huge pages created so far.
#How to create huge pages ? There are two ways:
- Add kernell boot parameter, e.g. "hugepagesz=2MB hugepages=16"
- Create on the fly, e.g. 'echo 16 > /sys/devices/system/node/node0/hugepages/hugepages-2048kB/nr_hugepages'
Verify if it is created:
#How to use these huge pages?
First, we need create a directory as mount point, then mount it like below:
Now /mnt/huge/ is ready to be used.
See examples:
1) map_hugetlb: see tools/testing/selftests/vm/map_hugetlb.c
2) hugepage-shm: see tools/testing/selftests/vm/hugepage-shm.c
3) hugepage-mmap: see tools/testing/selftests/vm/hugepage-mmap.c
4) The libhugetlbfs (https://github.com/libhugetlbfs/libhugetlbfs) library provides a wide range of userspace tools to help with huge page usability, environment setup, and control.
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--- layout: post title: "About Gin" permalink: /gin/index.html description: "Some description about Gin.." ---


Frequently Asked Questions
Try us for a month, we gaurentee you'll be happy. There is no fixed term, unless you want to pay for an annual plan, so you can cancel at any time. If you aren't completely satisfied, we provide a refund and call it a day.
When you say "bug fixes or minor enhancements tasks are included", what do you mean?
This includes any basic development or operations tasks, such as reviewing and fixing database inconsistency, replacing SSL certificates,
migrating or fixing DNS issues, or diagnosing and providing a quick bug fix. We know a big job when we see one and will let you know. In general, we are flexible.
Will you fix any crash/bug that happens?
Yep, or at least do our best to try depending on the complexity of the issue!
If I cancel, are the accounts and data you've collected transferable to me?
They sure are! We try to keep you owning all services from the begining so you can pull the plug at any time. Where that's not possible, we will arrange to have all the accounts transferred to you. This may involve you taking on the billing for the
accounts. Altneratively, and depending on the service, we will work with you to export your data and provide it to you.
Will you sign my NDA?
Maybe, we actually have good Mutual Non-Disclosure we can use. Just ask!
This seems a little expensive, isn't it?
Your web application is critical to your business. If you rely on a custom web application to drive your business, interact with your customers, and build your brand, you can't afford downtime, problems, or being in a situtation where you can't move foward. Customer's data loss is not acceptable. Will you lose sales due to bugs?
Maintaining a web application requires specialized knowledge of Ruby on Rails, Heroku and other web hosting providers, database servers, caching, gem versioning, and quick thinking that will keep your application running and optimized while you sleep.
Compare the cost of hiring a full-time employee, benefits, software, hardware, training, time spent learning your app, etc. If our monthly plans don't work for you, we can assist you in your hiring of such a person.


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Mega Pool 票池是由一群相信Decred治理模式的小伙伴发起运营。我们的使命是，与所有DCR持有者一起支持DCR的长期发展和演变。我们7x24小时在线，接受你的委托并进行投票。
权益证明和投票在Decred治理中扮演着举足轻重的角色，使得DCR持有者在DCR的治理上获得参与权和治理权：第一、DCR持有者投票验证PoW矿工挖到的每一个块，投票参与者会收到被验证区块的30%区块奖励做为PoS奖励；第二、DCR持有者参与DCR社区未来发展计划的决策。每一个参与的持币者共同决定了Decred的发展和未来。
投票的要求是，钱包需要7x24小时在线，以便在自己的选票被主网络随机征召到时可以迅速回应并投票。网络连接质量也会影响投票动作是否成功进行。所以，不具备7x24在线网络或者钱包的个人持币者参与投票无法保证较高的投票成功率，从而产生损失。
票池为解决这个问题应运而生，简单来说是由社区运营的在线钱包，你可以将自己的投票权委托与其并代由你进行投票。票池通常在全球多个地点部署钱包，保证多钱包冗余并可用。每个钱包需要有高可用的网络和服务器，保持与Decred网络的顺畅网络连接。如此一来，票池投票的丢票率就非常低。票池会收取一定费用（于我们，投票收益的1%）来支付运营票池网络和服务器的成本。
使用票池只会将你的投票权委托给票池，你的DCR币不会转移依然属于自己。票池无法拥有或染指你的资产/币，也没有办法获得你的钱包种子或者私钥。使用票池委托投票对你的资产/币是绝对安全的。
Decrd的权益证明系统使用了多重签名机制来委托投票权，委托后你或者票池均可为你的该选票投票。选票购买过程使用了共识承诺来保证最终投票收益将独立返还。你的投票收益会直接进入你的DCR币地址（不经过票池），补贴票池运营的投票委托费将单独进入票池地址。你的收益不经过票池，也不会和票池混杂。
票池受委托于你，在你的选票在被征召时行使投票权。票池无法触碰或盗取你的数字货币。
使用票池是持币者最好的参与Decred治理和权益证明投票的方式，在以下情况下：
· 当持币者无法7x24小时保持钱包在线并为解锁状态时；
· 当持币者无法保持非常稳定和低延迟的网络连接时。
获取票池源代码，请点击这里GitHub.
Mega Pool, a Decred Stake Pool, is set up and run by a group of strong believers of Decred governance mechanism. Our mission is to support the long-term development and evolution of Decred, together with all Decred holders. We are 24/7 online, waiting to vote on your behalf.
The Proof of Stake system and voting play a big role in Decred governance. It makes possible that holders of Decred have a say in the governance of the currency. 1) PoS stakers validate the blocks the PoW miners mine. The PoS system rewards participants by distributing 30% of every block reward to tickets chosen to vote in that block. 2) PoS stakers vote on an agenda of Decred community. The development and future are decided by every stakeholder who participate.
To be able to vote, a wallet needs to be online 24/7 to respond to a vote if one of your tickets is selected. The internet connection also affects whether a vote is successfully cast. Thus, solo voting by individuals not setting up with 24/7 servers are hard.
A stake pool is basically a community run wallet to which you can assign the voting rights of your tickets and the pool will vote on your behalf. A stake pool implements multi-wallet redundancy by having many wallets physically distributed around the globe. In addition, every wallet is supported by high availability and superspeed connection to the Decred network. Thus, there is very low chance of your vote being missed. A pool charges a small percentage of fee (with us, 1%) to support such network infrastructure.
You are only assigning voting rights to the pool, not your actual funds. A stake pool NEVER possesses or owns your assets, neither can a pool access your seeds or private keys. You are 100% SAFE to delegate your voting rights to a pool.
Decred PoS system adopts a multisig mechanism for delegating voting rights, which means either you or the pool can vote. The ticket purchase contains a consensus-enforced commitment for the final subsidy address. As a result, the PoS voting reward goes directly to your address, while the pool fee goes to support the operation of the pool. Your funds and rewards never get crossed with the pool.
A stake pool is used to delegate your voting powers to a third party (the pool). The pool CANNOT steal your funds.
Participating in a stake pool is perfect for people who wish to take part in Decred's proof of stake voting but can't due to:
· Not wanting to keep a constantly unlocked wallet
· Lack of a reliable/low latency Internet connection
The source code is available at GitHub.


3D Spline Range Chart
3D Range Chart
2D Range Column Chart
2D Spline Range Chart
2D Range Chart
2D Range Bar Chart


EXCLUSIVE: Tray Deee on 3 Qualities That Allowed Him to Avoid Death While Gang Banging
by VladTVIn this clip, Tray Deee explained why he characterizes the prison system as "forever punishment," and offered up some advice to those recently paroled on what measures to take to ensure they get support from the state. He also answered a viewer's question about the three main qualities that allowed him to successfully navigate gang and prison life.