Disp R-CNN
Disp R-CNN
**Disp R-CNN** is a 3D object detection system for stereo images. It utilizes an instance disparity estimation network (iDispNet) that predicts disparity only for pixels on objects of interest and learns a category-specific shape prior for more accurate disparity estimation. To address the challenge from scarcity of disparity annotation in training, a statistical shape model is used to generate dense disparity pseudo-ground-truth without the need of LiDAR point clouds.
Disp R-CNN: Stereo 3D Object Detection via Shape Prior Guided Instance Disparity Estimation
https://paperswithcode.com/paper/disp-r-cnn-stereo-3d-object-detection-via
Disp R-CNN: Stereo 3D Object Detection via Shape Prior Guided Instance Disparity Estimation