README.md

DR Loss

PyTorch Implementation for Our CVPR'20 Paper: "DR Loss: Improving Object Detection by Distributional Ranking"

Requirements

• Python 3.7
• PyTorch 1.1
• maskrcnn-benchmark

Usage:

1. Put the loss file to the codebase of maskrcnn_benchmark at

maskrcnn-benchmark/maskrcnn_benchmark/layers/sigmoid_dr_loss.py

and add the class into "init.py".

2. Change the focal loss in RetinaNet to the dr loss at

maskrcnn-benchmark/maskrcnn_benchmark/modeling/rpn/retinanet/loss.py

3. Run RetinaNet with the configurations in "configs/dr_retina".

Models:

model	lr sched	multi-scale training	mAP(minival)	mAP (test-dev)	link
Dr_Retina_R-50-FPN	1x	No	37.4	37.6	Google Drive
Dr_Retina_R-101-FPN	2x	Yes	41.5	41.7	Google Drive

Citation

If you use the package in your research, please cite our paper:

@inproceedings{qian2020dr,
  author    = {Qi Qian and
               Lei Chen and
               Hao Li and
               Rong Jin},
  title     = {DR Loss: Improving Object Detection by Distributional Ranking},
  booktitle = {{IEEE} Conference on Computer Vision and Pattern Recognition, {CVPR} 2020},
  year      = {2020}
}