MasterBin-IIAU / VisionTransformer

Awesome Transformer in Vision

A curated list of vision transformer related resources. Please feel free to pull requests or open an issue to add papers.

Table of Contents

• Awesome Surveys

• Transformer in Vision

  • 2021 Venues

  • 2020 Venues

  • 2019 Venues

  • Previous Venues

  • Awesome Libraies

Awesome Surveys

Title	Venue	BibTeX
A Survey on Visual Transformer	ArXiv	Bib

Transformer in Vision

Task	Reg	Det	Seg	Trk	Other
Explanation	Image Recoginition	Object Detection	Image Segmentation	Object Tracking	other types

You can add a tag for domains which contains several transformer-based works

2021

(Pls follow Time Inverse Ranking)

Title	Venue	Task	Code	BibTeX
Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet	Arxiv	Reg	GitHub	Bib @article{yuan2021tokens, title={Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet}, author={Yuan, Li and Chen, Yunpeng and Wang, Tao and Yu, Weihao and Shi, Yujun and Tay, Francis EH and Feng, Jiashi and Yan, Shuicheng}, journal={arXiv preprint arXiv:2101.11986}, year={2021} }
Bottleneck Transformers for Visual Recognition	Arxiv	Reg	GitHub	Bib @article{srinivas2021bottleneck, title={Bottleneck Transformers for Visual Recognition}, author={Srinivas, Aravind and Lin, Tsung-Yi and Parmar, Niki and Shlens, Jonathon and Abbeel, Pieter and Vaswani, Ashish}, journal={arXiv preprint arXiv:2101.11605}, year={2021} }
SSTVOS: Sparse Spatiotemporal Transformers for Video Object Segmentation	Arxiv	Seg	---	Bib @article{duke2021sstvos, title={SSTVOS: Sparse Spatiotemporal Transformers for Video Object Segmentation}, author={Duke, Brendan and Ahmed, Abdalla and Wolf, Christian and Aarabi, Parham and Taylor, Graham W}, journal={arXiv preprint arXiv:2101.08833}, year={2021} }
TrackFormer: Multi-Object Tracking with Transformers	Arxiv	Trk	---	Bib @article{meinhardt2021trackformer, title={TrackFormer: Multi-Object Tracking with Transformers}, author={Meinhardt, Tim and Kirillov, Alexander and Leal-Taixe, Laura and Feichtenhofer, Christoph}, journal={arXiv preprint arXiv:2101.02702}, year={2021} }

2020

Title	Venue	Task	Code	BibTeX
Training data-efficient image transformers & distillation through attention	ArXiv	Reg	GitHub	Bib @article{touvron2020training, title={Training data-efficient image transformers & distillation through attention}, author={Touvron, Hugo and Cord, Matthieu and Douze, Matthijs and Massa, Francisco and Sablayrolles, Alexandre and J{'e}gou, Herv{'e}}, journal={arXiv preprint arXiv:2012.12877}, year={2020} }
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale	ICLR	Reg	GitHub	Bib @article{dosovitskiy2020image, title={An image is worth 16x16 words: Transformers for image recognition at scale}, author={Dosovitskiy, Alexey and Beyer, Lucas and Kolesnikov, Alexander and Weissenborn, Dirk and Zhai, Xiaohua and Unterthiner, Thomas and Dehghani, Mostafa and Minderer, Matthias and Heigold, Georg and Gelly, Sylvain and others}, journal={arXiv preprint arXiv:2010.11929}, year={2020} }
Toward Transformer-Based Object Detection	ArXiv	Det	---	Bib @article{beal2020toward, title={Toward Transformer-Based Object Detection}, author={Beal, Josh and Kim, Eric and Tzeng, Eric and Park, Dong Huk and Zhai, Andrew and Kislyuk, Dmitry}, journal={arXiv preprint arXiv:2012.09958}, year={2020} }
Rethinking Transformer-based Set Prediction for Object Detection	ArXiv	Det	---	Bib @article{sun2020rethinking, title={Rethinking Transformer-based Set Prediction for Object Detection}, author={Sun, Zhiqing and Cao, Shengcao and Yang, Yiming and Kitani, Kris}, journal={arXiv preprint arXiv:2011.10881}, year={2020} }
UP-DETR: Unsupervised Pre-training for Object Detection with Transformers	ArXiv	Det	---	Bib @article{dai2020up, title={UP-DETR: Unsupervised Pre-training for Object Detection with Transformers}, author={Dai, Zhigang and Cai, Bolun and Lin, Yugeng and Chen, Junying}, journal={arXiv preprint arXiv:2011.09094}, year={2020} }
Deformable DETR: Deformable Transformers for End-to-End Object Detection	ArXiv	Det	GitHub	Bib @article{zhu2020deformable, title={Deformable DETR: Deformable Transformers for End-to-End Object Detection}, author={Zhu, Xizhou and Su, Weijie and Lu, Lewei and Li, Bin and Wang, Xiaogang and Dai, Jifeng}, journal={arXiv preprint arXiv:2010.04159}, year={2020} }
End-to-End Object Detection with Transformers	ECCV	Det	GitHub	Bib article{zhu2020deformable, title={Deformable DETR: Deformable Transformers for End-to-End Object Detection}, author={Zhu, Xizhou and Su, Weijie and Lu, Lewei and Li, Bin and Wang, Xiaogang and Dai, Jifeng}, journal={arXiv preprint arXiv:2010.04159}, year={2020} }
Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers	Arxiv	Seg	Github	Bib @article{zheng2020rethinking, title={Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers}, author={Zheng, Sixiao and Lu, Jiachen and Zhao, Hengshuang and Zhu, Xiatian and Luo, Zekun and Wang, Yabiao and Fu, Yanwei and Feng, Jianfeng and Xiang, Tao and Torr, Philip HS and others}, journal={arXiv preprint arXiv:2012.15840}, year={2020} }
MaX-DeepLab: End-to-End Panoptic Segmentation with Mask Transformers	Arxiv	Seg	---	Bib @article{wang2020max, title={MaX-DeepLab: End-to-End Panoptic Segmentation with Mask Transformers}, author={Wang, Huiyu and Zhu, Yukun and Adam, Hartwig and Yuille, Alan and Chen, Liang-Chieh}, journal={arXiv preprint arXiv:2012.00759}, year={2020} }
TransTrack: Multiple-Object Tracking with Transformer	ArXiv	Trk	GitHub	Bib @article{sun2020transtrack, title={TransTrack: Multiple-Object Tracking with Transformer}, author={Sun, Peize and Jiang, Yi and Zhang, Rufeng and Xie, Enze and Cao, Jinkun and Hu, Xinting and Kong, Tao and Yuan, Zehuan and Wang, Changhu and Luo, Ping}, journal={arXiv preprint arXiv:2012.15460}, year={2020} }

2012-2019

Title	Venue	Task	Code	BibTeX
Attention Is All You Need	NeurIPS'17	--	GitHub	Bib @inproceedings{vaswani2017attention, title={Attention is all you need}, author={Vaswani, Ashish and Shazeer, Noam and Parmar, Niki and Uszkoreit, Jakob and Jones, Llion and Gomez, Aidan N and Kaiser, {\L}ukasz and Polosukhin, Illia}, booktitle={Advances in neural information processing systems}, pages={5998--6008}, year={2017} }

Awesome vTransformer Libraies

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