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SOTA2 Research · papers
Find papers, implementations, and the benchmark evidence behind state-of-the-art AI systems.
| 2021 |
| arxiv 2101.12482 |
| Adaptive Poincar\'e Point to Set Distance for Few-Shot Classification | Rongkai Ma, Pengfei Fang, Tom Drummond | 2021 | arxiv 2112.01719 |
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| Co-training Transformer with Videos and Images Improves Action Recognition | Bowen Zhang, Jiahui Yu, Christopher Fifty | 2021 | arxiv 2112.07175 |
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| Multi-Label Classification on Remote-Sensing Images | Aditya Kumar Singh, B. Uma Shankar | 2022 | arxiv 2201.01971 |
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| When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations | Xiangning Chen, Cho-Jui Hsieh, Boqing Gong | 2021 | arxiv 2106.01548 |
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| UniVIP: A Unified Framework for Self-Supervised Visual Pre-training | Zhaowen Li, Yousong Zhu, Fan Yang | 2022 | arxiv 2203.06965 |
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| Crafting Better Contrastive Views for Siamese Representation Learning | Xiangyu Peng, Kai Wang, Zheng Zhu | 2022 | arxiv 2202.03278 |
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| Boost Test-Time Performance with Closed-Loop Inference | Shuaicheng Niu, Jiaxiang Wu, Yifan Zhang | 2022 | arxiv 2203.10853 |
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| PatchCleanser: Certifiably Robust Defense against Adversarial Patches for Any Image Classifier | Chong Xiang, Saeed Mahloujifar, Prateek Mittal | 2021 | arxiv 2108.09135 |
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| A Simple Recipe for Competitive Low-compute Self supervised Vision Models | Quentin Duval, Ishan Misra, Nicolas Ballas | 2023 | arxiv 2301.09451 |
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| Training trajectories, mini-batch losses and the curious role of the learning rate | Mark Sandler, Andrey Zhmoginov, Max Vladymyrov | 2023 | arxiv 2301.02312 |
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