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In recent advancements in unsupervised visual representation learning, the Joint-Embedding Predictive Architecture (JEPA) has emerged as a significant method for extracting visual features from unlabeled imagery through an innovative masking strategy.
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Microsoft coco: Common objects in context
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The 2017 davis challenge on video object segmentation
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Bolei Zhou, Hang Zhao, Xavier Puig, Sanja Fidler, Adela Barriuso, and Antonio Torralba · 2018
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Jaehoon Lee, Lechao Xiao, Samuel S Schoenholz, Yasaman Bahri, Roman Novak, Jascha Sohl-Dickstein, and Jeffrey Pennington · 2019
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Ilya Loshchilov and Frank Hutter · 2019
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Big self-supervised models are strong semi-supervised learners
Ting Chen, Simon Kornblith, Kevin Swersky, Mohammad Norouzi, and Geoffrey Hinton · 2020
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Jean-Bastien Grill, Florian Strub, Florent Altché, Corentin Tallec, Pierre Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Avila Pires, Zhaohan Guo, Mohammad Gheshlaghi Azar, Bilal Piot, koray kavukcuoglu, Remi Munos, and Michal Valko · 2020
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Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2020
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Xinlei Chen, Haoqi Fan, Ross Girshick, and Kaiming He · 2020
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Supervised contrastive learning
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Zhenda Xie, Zheng Zhang, Yue Cao, Yutong Lin, Jianmin Bao, Zhuliang Yao, Qi Dai, and Han Hu · 2022
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Object-wise masked autoencoders for fast pre-training
Jiantao Wu and Shentong Mo · 2022
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Context autoencoder for self-supervised representation learning
Xiaokang Chen, Mingyu Ding, Xiaodi Wang, Ying Xin, Shentong Mo, Yunhao Wang, Shumin Han, Ping Luo, Gang Zeng, and Jingdong Wang · 2022
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Adversarial masking for self-supervised learning
Yuge Shi, N Siddharth, Philip HS Torr, and Adam R Kosiorek · 2022
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MVP: multimodality-guided visual pre-training
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Hangbo Bao, Li Dong, and Furu Wei · 2021
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Sara Atito, Muhammad Awais, and Josef Kittler · 2021
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Kaiming He, Xinlei Chen, Saining Xie, Yanghao Li, Piotr Dollár, and Ross B. Girshick · 2021
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MST: Masked self-supervised transformer for visual representation
Zhaowen Li, Zhiyang Chen, Fan Yang, Wei Li, Yousong Zhu, Chaoyang Zhao, Rui Deng, Liwei Wu, Rui Zhao, Ming Tang, and Jinqiao Wang · 2021
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Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever · 2021
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Hu Qianjiang, Wang Xiao, Hu Wei, and Qi Guo-Jun · 2021
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Prototypical contrastive learning of unsupervised representations
Junnan Li, Pan Zhou, Caiming Xiong, and Steven Hoi · 2021
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SemMAE: Semantic-guided masking for learning masked autoencoders
Gang Li, Heliang Zheng, Daqing Liu, Chaoyue Wang, Bing Su, and Changwen Zheng · 2022
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ibot: Image bert pre-training with online tokenizer
Jinghao Zhou, Chen Wei, Huiyu Wang, Wei Shen, Cihang Xie, Alan Yuille, and Tao Kong · 2022
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Alexei Baevski, Wei-Ning Hsu, Qiantong Xu, Arun Babu, Jiatao Gu, and Michael Auli · 2022
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Masked momentum contrastive learning for zero-shot semantic understanding
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Jiantao Wu, Shentong Mo, Sara Atito, Josef Kittler, Zhenhua Feng, and Muhammad Awais · 2023
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Representation disentanglement in generative models with contrastive learning
Shentong Mo, Zhun Sun, and Chao Li · 2023
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Multi-level contrastive learning for self-supervised vision transformers
Shentong Mo, Zhun Sun, and Chao Li · 2023
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Yubei Chen, Adrien Bardes, ZENGYI LI, and Yann LeCun · 2023
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Implicit variance regularization in non-contrastive SSL
Manu Srinath Halvagal, Axel Laborieux, and Friedemann Zenke · 2023
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Revisiting feature prediction for learning visual representations from video
Adrien Bardes, Quentin Garrido, Jean Ponce, Xinlei Chen, Michael Rabbat, Yann LeCun, Mahmoud Assran, and Nicolas Ballas · 2024
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Dailymae: Towards pretraining masked autoencoders in one day
Jiantao Wu, Shentong Mo, Sara Atito, Zhenhua Feng, Josef Kittler, and Muhammad Awais · 2024
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Dmt-jepa: Discriminative masked targets for joint-embedding predictive architecture
Shentong Mo and Sukmin Yun · 2024
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