Ood-cv: A benchmark for robustness to out-of-distribution shifts of individual nuisances in natural images B Zhao, S Yu, W Ma, M Yu, S Mei, A Wang, J He, A Yuille, A Kortylewski European conference on computer vision, 163-180, 2022 | 59* | 2022 |
Rethinking out-of-distribution (ood) detection: Masked image modeling is all you need J Li, P Chen, Z He, S Yu, S Liu, J Jia Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2023 | 43 | 2023 |
The 1st agriculture-vision challenge: Methods and results MT Chiu, X Xu, K Wang, J Hobbs, N Hovakimyan, TS Huang, H Shi Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 33 | 2020 |
Rail-5k: A real-world dataset for rail surface defects detection Z Zhang, S Yu, S Yang, Y Zhou, B Zhao arXiv preprint arXiv:2106.14366, 2021 | 14 | 2021 |
Reducing the feature divergence of rgb and near-infrared images using switchable normalization S Yang, S Yu, B Zhao, Y Wang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 13 | 2020 |
Long alpaca: Long-context instruction-following models Y Chen, S Yu, S Qian, H Tang, X Lai, Z Liu, S Han, J Jia | 7 | 2023 |
MOODv2: Masked Image Modeling for Out-of-Distribution Detection J Li, P Chen, S Yu, S Liu, J Jia IEEE transactions on pattern analysis and machine intelligence, 2024 | 6 | 2024 |
OOD-CV-v2: An extended benchmark for robustness to out-of-distribution shifts of individual nuisances in natural images B Zhao, J Wang, W Ma, A Jesslen, S Yang, S Yu, O Zendel, C Theobalt, ... IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024 | 5 | 2024 |
Bal: Balancing diversity and novelty for active learning J Li, P Chen, S Yu, S Liu, J Jia IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 | 4 | 2023 |
Making CNNs Interpretable by Building Dynamic Sequential Decision Forests with Top-down Hierarchy Learning Y Wang, S Yu, X Yang, W Shen arXiv preprint arXiv:2106.02824, 2021 | 1 | 2021 |