标题/作者	年份
Masked autoencoders are scalable vision learners K He, X Chen, S Xie, Y Li, P Dollár, R Girshick Proceedings of the IEEE/CVF conference on computer vision and pattern …	2022
Multiscale vision transformers H Fan, B Xiong, K Mangalam, Y Li, Z Yan, J Malik, C Feichtenhofer Proceedings of the IEEE/CVF international conference on computer vision …	2021
Beit: Bert pre-training of image transformers H Bao, L Dong, S Piao, F Wei arXiv preprint arXiv:2106.08254	2021
On the opportunities and risks of foundation models R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ... arXiv preprint arXiv:2108.07258	2021
Transformers in vision: A survey S Khan, M Naseer, M Hayat, SW Zamir, FS Khan, M Shah ACM computing surveys (CSUR) 54 (10s), 1-41	2022
Unetr: Transformers for 3d medical image segmentation A Hatamizadeh, Y Tang, V Nath, D Yang, A Myronenko, B Landman, ... Proceedings of the IEEE/CVF winter conference on applications of computer …	2022
Scaling vision transformers X Zhai, A Kolesnikov, N Houlsby, L Beyer Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …	2022
Attention mechanisms in computer vision: A survey MH Guo, TX Xu, JJ Liu, ZN Liu, PT Jiang, TJ Mu, SH Zhang, RR Martin, ... Computational visual media 8 (3), 331-368	2022
Simmim: A simple framework for masked image modeling Z Xie, Z Zhang, Y Cao, Y Lin, J Bao, Z Yao, Q Dai, H Hu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …	2022
Do vision transformers see like convolutional neural networks? M Raghu, T Unterthiner, S Kornblith, C Zhang, A Dosovitskiy Advances in Neural Information Processing Systems 34, 12116-12128	2021
Simvlm: Simple visual language model pretraining with weak supervision Z Wang, J Yu, AW Yu, Z Dai, Y Tsvetkov, Y Cao arXiv preprint arXiv:2108.10904	2021
ibot: Image bert pre-training with online tokenizer J Zhou, C Wei, H Wang, W Shen, C Xie, A Yuille, T Kong arXiv preprint arXiv:2111.07832	2021
Intriguing properties of vision transformers MM Naseer, K Ranasinghe, SH Khan, M Hayat, F Shahbaz Khan, ... Advances in Neural Information Processing Systems 34, 23296-23308	2021
Masked feature prediction for self-supervised visual pre-training C Wei, H Fan, S Xie, CY Wu, A Yuille, C Feichtenhofer Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …	2022
How to train your vit? data, augmentation, and regularization in vision transformers A Steiner, A Kolesnikov, X Zhai, R Wightman, J Uszkoreit, L Beyer arXiv preprint arXiv:2106.10270	2021
Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation N Ruiz, Y Li, V Jampani, Y Pritch, M Rubinstein, K Aberman Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …	2023
Scaling up your kernels to 31x31: Revisiting large kernel design in cnns X Ding, X Zhang, J Han, G Ding Proceedings of the IEEE/CVF conference on computer vision and pattern …	2022
Focal self-attention for local-global interactions in vision transformers J Yang, C Li, P Zhang, X Dai, B Xiao, L Yuan, J Gao arXiv preprint arXiv:2107.00641	2021
Xcit: Cross-covariance image transformers A Ali, H Touvron, M Caron, P Bojanowski, M Douze, A Joulin, I Laptev, ... Advances in neural information processing systems 34, 20014-20027	2021
With a little help from my friends: Nearest-neighbor contrastive learning of visual representations D Dwibedi, Y Aytar, J Tompson, P Sermanet, A Zisserman Proceedings of the IEEE/CVF International Conference on Computer Vision …	2021

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