dab_deformable_detr

DAB-Deformable-DETR

Implement DAB-Deformable-DETR which is a strong baseline of DAB-DETR: Dynamic Anchor Boxes are Better Queries for DETR.

[arXiv] [BibTeX]

Pretrained Models

Here we provide the pretrained DAB-Deformable-DETR weights based on detrex.

Name	Backbone	Pretrain	Epochs	box AP	download
DAB-Deformable-DETR-R50	R-50	IN1k	50	49.0	model
DAB-Deformable-DETR-R50-Two-Stage	R-50	IN1k	50	49.7	model

Training

All configs can be trained with:

cd detrex
python tools/train_net.py --config-file projects/dab_deformable_detr/configs/path/to/config.py --num-gpus 8

By default, we use 8 GPUs with total batch size as 16 for training.

Evaluation

Model evaluation can be done as follows:

cd detrex
python tools/train_net.py --config-file projects/dab_deformable_detr/configs/path/to/config.py --eval-only train.init_checkpoint=/path/to/model_checkpoint

Citing DAB-DETR

If you find our work helpful for your research, please consider citing the following BibTeX entry.

@inproceedings{
      liu2022dabdetr,
      title={{DAB}-{DETR}: Dynamic Anchor Boxes are Better Queries for {DETR}},
      author={Shilong Liu and Feng Li and Hao Zhang and Xiao Yang and Xianbiao Qi and Hang Su and Jun Zhu and Lei Zhang},
      booktitle={International Conference on Learning Representations},
      year={2022},
      url={https://openreview.net/forum?id=oMI9PjOb9Jl}
}