hust-lidelong / awesome-detection-transformer

Collect some papers about transformer for detection and segmentation. Awesome Detection Transformer for Computer Vision (CV)

Awesome Detection Transformer

This a collecttion of papers for detection and segmentation with Transformer .
If you find some overlooked papers or resourses, please open issues or pull requests (recommended).

Papers

2022

DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection.
Hao Zhang*, Feng Li*, Shilong Liu*, Lei Zhang, Hang Su, Jun Zhu, Lionel M. Ni, Heung-Yeung Shum
arxiv 2022. [paper] [code]

DN-DETR: Accelerate DETR Training by Introducing Query DeNoising.
Feng Li*, Hao Zhang*, Shilong Liu, Jian Guo, Lionel M. Ni, Lei Zhang.
CVPR 2022. [paper] [code]

DAB-DETR: Dynamic Anchor Boxes are Better Queries for DETR.
Shilong Liu, Feng Li, Hao Zhang, Xiao Yang, Xianbiao Qi, Hang Su, Jun Zhu, Lei Zhang.
ICLR 2022. [paper] [code]

FP-DETR: Detection Transformer Advanced by Fully Pre-training.
Wen Wang, Yang Cao, Jing Zhang, Dacheng Tao.
ICLR 2022. [paper]

D^2ETR: Decoder-Only DETR with Computationally Efficient Cross-Scale Attention.
Junyu Lin, Xiaofeng Mao, Yuefeng Chen, Lei Xu, Yuan He, Hui Xue
arxiv 2022. [paper]

Sparse DETR: Efficient End-to-End Object Detection with Learnable Sparsity.
Byungseok Roh, JaeWoong Shin, Wuhyun Shin, Saehoon Kim.
ICLR 2022. [paper] [code]

Anchor DETR: Query Design for Transformer-Based Object Detection.
Yingming Wang, Xiangyu Zhang, Tong Yang, Jian Sun.
AAAI 2022. [paper] [code]

2021

[Mask2Former] Masked-attention Mask Transformer for Universal Image Segmentation .
Bowen Cheng, Ishan Misra, Alexander G. Schwing, Alexander Kirillov, Rohit Girdhar.
arxiv 2021. [paper] [code]

[MaskFormer] Per-Pixel Classification is Not All You Need for Semantic Segmentation.
Bowen Cheng, Alexander G. Schwing, Alexander Kirillov.
NeurIPS 2021. [paper] [code]

[YOLOS] You Only Look at One Sequence: Rethinking Transformer in Vision through Object Detection.
Yuxin Fang*, Bencheng Liao*, Xinggang Wang, Jiemin Fang, Jiyang Qi, Rui Wu, Jianwei Niu, Wenyu Liu.
NeurIPS 2021. [paper] [code]

Dynamic DETR: End-to-End Object Detection With Dynamic Attention.
Xiyang Dai, Yinpeng Chen, Jianwei Yang, Pengchuan Zhang, Lu Yuan, Lei Zhang.
ICCV 2021. [paper]

PnP-DETR: Towards Efficient Visual Analysis with Transformers.
Tao Wang, Li Yuan, Yunpeng Chen, Jiashi Feng, Shuicheng Yan.
ICCV 2021. [paper] [code]

Conditional DETR for Fast Training Convergence.
Depu Meng*, Xiaokang Chen*, Zejia Fan, Gang Zeng, Houqiang Li, Yuhui Yuan, Lei Sun, Jingdong Wang.
ICCV 2021. [paper] [code]

Rethinking Transformer-based Set Prediction for Object Detection.
Zhiqing Sun, Shengcao Cao, Yiming Yang, Kris Kitani.
ICCV 2021. [paper] [code]

Fast Convergence of DETR with Spatially Modulated Co-Attention.
Peng Gao, Minghang Zheng, Xiaogang Wang, Jifeng Dai, Hongsheng Li .
ICCV 2021. [paper] [code]

MDETR -- Modulated Detection for End-to-End Multi-Modal Understanding.
Aishwarya Kamath, Mannat Singh, Yann LeCun, Gabriel Synnaeve, Ishan Misra, Nicolas Carion.
ICCV 2021. [paper] [code]

Efficient DETR: Improving End-to-End Object Detector with Dense Prior.
Zhuyu Yao, Jiangbo Ai, Boxun Li, Chi Zhang.
arxiv 2021. [paper]

UP-DETR: Unsupervised Pre-training for Object Detection with Transformers.
Zhigang Dai, Bolun Cai, Yugeng Lin, Junying Chen.
CVPR 2021. [paper] [code]

Deformable DETR: Deformable Transformers for End-to-End Object Detection.
Xizhou Zhu, Weijie Su, Lewei Lu, Bin Li, Xiaogang Wang, Jifeng Dai.
ICLR 2021. [paper] [code]

2020

[DETR] End-to-End Object Detection with Transformers.
Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, Sergey Zagoruyko.
ECCV 2020. [paper] [code]

Acknowledgements

We thank all the authors above for their great works!