# Group DETR: Fast DETR training with group-wise one-to-many assignment
# Group DETR v2: Strong object detector with encoder-decoder pretraining
## Introduction
[Group DETR](https://arxiv.org/pdf/2207.13085.pdf) is an object detection model based on DETR. We reproduced the model of the paper.
[Group DETR v2](https://arxiv.org/pdf/2211.03594.pdf) is a strong object detection model based on DINO and Group DETR. We reproduced the model of the paper.
## Model Zoo
| Backbone | Model | Epochs | Resolution |Box AP | Config | Download |
- Group DETR is trained on COCO train2017 dataset and evaluated on val2017 results of `mAP(IoU=0.5:0.95)`.
- Group DETRv2 requires a ViT-Huge encoder pre-trained and fine-tuned on ImageNet-1K in a self-supervised manner, a detector pre-trained on Object365, and finally it is fine-tuned on trainCOCO. Group DETRv2 is also evaluated on val2017 results of `mAP(IoU=0.5:0.95)`.
- Group DETR and Group DETRv2 are both use 4GPU to train.
title={Group DETR: Fast DETR training with group-wise one-to-many assignment},
author={Chen, Qiang and Chen, Xiaokang and Wang, Jian and Feng, Haocheng and Han, Junyu and Ding, Errui and Zeng, Gang and Wang, Jingdong},
journal={arXiv preprint arXiv:2207.13085},
volume={1},
number={2},
year={2022}
}
@article{chen2022group,
title={Group DETR v2: Strong object detector with encoder-decoder pretraining},
author={Chen, Qiang and Wang, Jian and Han, Chuchu and Zhang, Shan and Li, Zexian and Chen, Xiaokang and Chen, Jiahui and Wang, Xiaodi and Han, Shuming and Zhang, Gang and others},