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This technical report presents LongViT, a vision Transformer that can process gigapixel images in an end-to-end manner.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Earlier work this paper cites.
Deep sets
Manzil Zaheer, Satwik Kottur, Siamak Ravanbakhsh, Barnabás Póczos, Ruslan Salakhutdinov, and Alexander J. Smola · 2017
Earlier work this paper cites.
Attention-based deep multiple instance learning
Maximilian Ilse, Jakub M. Tomczak, and Max Welling · 2018
Earlier work this paper cites.
An integrated tcga pan-cancer clinical data resource to drive high-quality survival outcome analytics
Jianfang Liu, Tara Lichtenberg, Katherine A Hoadley, Laila M Poisson, Alexander J Lazar, Andrew D Cherniack, Albert J Kovatich, Christopher C Benz, Douglas A Levine, Adrian V Lee, et al · 2018
Earlier work this paper cites.
An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
Earlier work this paper cites.
Data efficient and weakly supervised computational pathology on whole slide images
Ming Y. Lu, Drew F. K. Williamson, Tiffany Y. Chen, Richard J. Chen, Matteo Barbieri, and Faisal Mahmood · 2020
Earlier work this paper cites.
Training data-efficient image transformers & distillation through attention
Hugo Touvron, Matthieu Cord, Matthijs Douze, Francisco Massa, Alexandre Sablayrolles, and Hervé Jégou · 2020
Cited alongside, same era.
Whole slide images based cancer survival prediction using attention guided deep multiple instance learning networks
Jiawen Yao, Xinliang Zhu, Jitendra Jonnagaddala, Nicholas J. Hawkins, and Junzhou Huang · 2020
Cited alongside, same era.
Predicting lymph node metastasis using histopathological images based on multiple instance learning with deep graph convolution
Yu Zhao, Fan Yang, Yuqi Fang, Hailing Liu, Niyun Zhou, Jun Zhang, Jiarui Sun, Sen Yang, Bjoern H. Menze, Xinjuan Fan, and Jianhua Yao · 2020
Cited alongside, same era.
Multimodal co-attention transformer for survival prediction in gigapixel whole slide images
Richard J. Chen, Ming Y. Lu, Wei-Hung Weng, Tiffany Y. Chen, Drew F. K. Williamson, Trevor Manz, Maha Shady, and Faisal Mahmood · 2021
Cited alongside, same era.
Emerging properties in self-supervised vision transformers
Dual-stream multiple instance learning network for whole slide image classification with self-supervised contrastive learning
Bin Li, Yin Li, and Kevin W. Eliceiri · 2021
Later among the works it cites.
Transmil: Transformer based correlated multiple instance learning for whole slide image classification
Zhuchen Shao, Hao Bian, Yang Chen, Yifeng Wang, Jian Zhang, Xiangyang Ji, et al · 2021
Later among the works it cites.
BEiT: BERT pre-training of image transformers
Hangbo Bao, Li Dong, Songhao Piao, and Furu Wei · 2022
Later among the works it cites.
Scaling vision transformers to gigapixel images via hierarchical self-supervised learning
Richard J. Chen, Chengkuan Chen, Yicong Li, Tiffany Y. Chen, Andrew D. Trister, Rahul G. Krishnan, and Faisal Mahmood · 2022
Later among the works it cites.
Longnet: Scaling transformers to 1, 000, 000, 000 tokens
Jiayu Ding, Shuming Ma, Li Dong, Xingxing Zhang, Shaohan Huang, Wenhui Wang, Nanning Zheng, and Furu Wei · 2023
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Mathilde Caron, Hugo Touvron, Ishan Misra, Hervé Jégou, Julien Mairal, Piotr Bojanowski, and Armand Joulin · 2021
Cited alongside, same era.
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