Deformable DETR
Deformable DETR
**Deformable DETR** is an object detection method that aims mitigates the slow convergence and high complexity issues of [DETR](https://www.paperswithcode.com/method/detr). It combines the best of the sparse spatial sampling of [deformable convolution](https://paperswithcode.com/method/deformable-convolution), and the relation modeling capability of [Transformers](https://paperswithcode.com/methods/category/transformers). Specifically, it introduces a 
 deformable attention module, which attends to a small set of sampling locations as a pre-filter for prominent key elements out of all the feature map pixels. The module can be naturally extended to aggregating multi-scale features, without the help of [FPN](https://paperswithcode.com/method/fpn).
Deformable DETR: Deformable Transformers for End-to-End Object Detection
https://paperswithcode.com/paper/deformable-detr-deformable-transformers-for-1
Deformable DETR: Deformable Transformers for End-to-End Object Detection