The code includes training and inference procedures for Beyond Max-Margin: Class Margin Equilibrium for Few-shot Object Detection(CVPR2021).

Our code is based on https://github.com/bingykang/Fewshot_Detection and developed with Python 3.6.5 & PyTorch 1.1.0.

If you want to train our model on VOC pascal dataset, please prepare dataset according to https://github.com/bingykang/Fewshot_Detection

If you finish preparing dataset, Please modify the dir in train_decoupling_disturbance.py and valid_decoupling.py

sys.path.append("Your Project dir")

After that,you can

bash train_model.sh

to train model and get corresponding results on split1. If you want to train other split, you only need to change

SPLIT=(1)

to which split you want to train.

You can download the pretrained weight by Google Drive or BaiduYun with code: CVPR

@InProceedings{Li_2021_CVPR,
  author = {Bohao Li, Boyu Yang, Chang Liu, Feng Liu, Rongrong Ji and Qixiang Ye},
  title = {Beyond Max-Margin: Class Margin Equilibrium for Few-shot Object Detection},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  month = {June},
  year = {2021}
}