Zhi Cai, Songtao Liu, Guodong Wang, Zheng Ge, Xiangyu Zhang, Di Huang
[arXiv
] [BibTex
] [Official Implementation
]
AlignDETR is a variant of DETR(DEtection with Transformer), with a simple IoU-Aware BCE loss and better performance! It aims to solve the issue of misalignment problem spotted in DETR's output.
Train Example
python tools/train_net.py --config-file aligndetr/aligndetr_k=2_r50_4scale_12ep.py --num-gpus 8
Evaluation Example
python tools/train_net.py --config-file aligndetr/aligndetr_k=2_r50_4scale_12ep.py --num-gpus 8 --eval train.init_checkpoint=/path/to/checkpoint
Model | AP | AP50 | AP75 | APs | APm | APl | weights |
---|---|---|---|---|---|---|---|
AlignDETR-R50-12ep | 50.3 | 67.9 | 54.8 | 34.1 | 53.5 | 65.1 | Google Drive |
AlignDETR-R50-24ep | 51.4 | 69.1 | 55.8 | 35.5 | 54.6 | 65.7 | Google Drive |
Our code is based on detrex and detectron2.
If you are interested in our work and use our method in your research, please cite
@misc{cai2023aligndetr,
title={Align-DETR: Improving DETR with Simple IoU-aware BCE loss},
author={Zhi Cai and Songtao Liu and Guodong Wang and Zheng Ge and Xiangyu Zhang and Di Huang},
year={2023},
eprint={2304.07527},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
This project is released under the Apache 2.0 license.