Semmae: Semantic-guided masking for learning masked autoencoders G Li, H Zheng, D Liu, C Wang, B Su, C Zheng Advances in Neural Information Processing Systems 35, 14290-14302, 2022 | 115 | 2022 |
A molecular multimodal foundation model associating molecule graphs with natural language B Su, D Du, Z Yang, Y Zhou, J Li, A Rao, H Sun, Z Lu, JR Wen arXiv preprint arXiv:2209.05481, 2022 | 114* | 2022 |
Order-preserving wasserstein distance for sequence matching B Su, G Hua Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 76 | 2017 |
Preformer: predictive transformer with multi-scale segment-wise correlations for long-term time series forecasting D Du, B Su, Z Wei ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 61 | 2023 |
Online joint multi-metric adaptation from frequent sharing-subset mining for person re-identification J Zhou, B Su, Y Wu Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 59 | 2020 |
Discriminative dimensionality reduction for multi-dimensional sequences B Su, X Ding, H Wang, Y Wu IEEE transactions on pattern analysis and machine intelligence 40 (1), 77-91, 2017 | 56 | 2017 |
Order-preserving optimal transport for distances between sequences B Su, G Hua IEEE transactions on pattern analysis and machine intelligence 41 (12), 2961 …, 2018 | 41 | 2018 |
Self-supervised action representation learning from partial spatio-temporal skeleton sequences Y Zhou, H Duan, A Rao, B Su, J Wang Proceedings of the AAAI Conference on Artificial Intelligence 37 (3), 3825-3833, 2023 | 38 | 2023 |
Metaug: Contrastive learning via meta feature augmentation J Li, W Qiang, C Zheng, B Su, H Xiong International Conference on Machine Learning, 12964-12978, 2022 | 36 | 2022 |
Linear sequence discriminant analysis: a model-based dimensionality reduction method for vector sequences B Su, X Ding Proceedings of the IEEE International Conference on Computer Vision, 889-896, 2013 | 35 | 2013 |
Interventional contrastive learning with meta semantic regularizer W Qiang, J Li, C Zheng, B Su, H Xiong International Conference on Machine Learning, 18018-18030, 2022 | 33 | 2022 |
Heteroscedastic max-min distance analysis B Su, X Ding, C Liu, Y Wu Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015 | 31 | 2015 |
Hierarchical dynamic parsing and encoding for action recognition B Su, J Zhou, X Ding, H Wang, Y Wu Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 30 | 2016 |
Robust local preserving and global aligning network for adversarial domain adaptation W Qiang, J Li, C Zheng, B Su, H Xiong IEEE Transactions on Knowledge and Data Engineering 35 (3), 3014-3029, 2021 | 28 | 2021 |
Unsupervised hierarchical dynamic parsing and encoding for action recognition B Su, J Zhou, X Ding, Y Wu IEEE Transactions on Image Processing 26 (12), 5784-5799, 2017 | 24 | 2017 |
Transfer knowledge from head to tail: Uncertainty calibration under long-tailed distribution J Chen, B Su Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2023 | 23 | 2023 |
Easy identification from better constraints: Multi-shot person re-identification from reference constraints J Zhou, B Su, Y Wu Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 20 | 2018 |
Meta attention-generation network for cross-granularity few-shot learning W Qiang, J Li, B Su, J Fu, H Xiong, JR Wen International Journal of Computer Vision 131 (5), 1211-1233, 2023 | 19 | 2023 |
Modeling video as stochastic processes for fine-grained video representation learning H Zhang, D Liu, Q Zheng, B Su Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 19 | 2023 |
A novel baseline-independent feature set for arabic handwriting recognition B Su, X Ding, L Peng, C Liu 2013 12th International Conference on Document Analysis and Recognition …, 2013 | 19 | 2013 |