| Expectation-maximization attention networks for semantic segmentation X Li, Z Zhong, J Wu, Y Yang, Z Lin, H Liu Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 749 | 2019 |
| Spatial pyramid based graph reasoning for semantic segmentation X Li*, Y Yang*, Q Zhao, T Shen, Z Lin, H Liu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 221 | 2020 |
| Convolutional neural networks with alternately updated clique Y Yang, Z Zhong, T Shen, Z Lin Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 158 | 2018 |
| TransVOD: End-to-end Video Object Detection with Spatial-Temporal Transformers Q Zhou, X Li, L He, Y Yang, G Cheng, Y Tong, L Ma, D Tao IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 | 157 | 2022 |
| Neural collapse inspired feature-classifier alignment for few-shot class incremental learning Y Yang, H Yuan, X Li, Z Lin, P Torr, D Tao ICLR 2023, 2023 | 146 | 2023 |
| Towards open vocabulary learning: A survey J Wu, X Li, S Xu, H Yuan, H Ding, Y Yang, X Li, J Zhang, Y Tong, X Jiang, ... IEEE Transactions on Pattern Analysis and Machine Intelligence 46 (7), 5092-5113, 2024 | 131 | 2024 |
| Inducing Neural Collapse in Imbalanced Learning: Do We Really Need a Learnable Classifier at the End of Deep Neural Network? Y Yang, S Chen, X Li, L Xie, Z Lin, D Tao Advances in Neural Information Processing Systems 35, 37991-38002, 2022 | 127 | 2022 |
| Joint sub-bands learning with clique structures for wavelet domain super-resolution Z Zhong, T Shen, Y Yang, Z Lin, C Zhang Advances in Neural Information Processing Systems 31, 165-175, 2018 | 83 | 2018 |
| Sognet: Scene overlap graph network for panoptic segmentation Y Yang, H Li, X Li, Q Zhao, J Wu, Z Lin Proceedings of the AAAI Conference on Artificial Intelligence 34 (07), 12637 …, 2020 | 76 | 2020 |
| View vertically: A hierarchical network for trajectory prediction via fourier spectrums C Wong, B Xia, Z Hong, Q Peng, W Yuan, Q Cao, Y Yang, X You European Conference on Computer Vision, 682-700, 2022 | 69 | 2022 |
| Ista-nas: Efficient and consistent neural architecture search by sparse coding Y Yang, H Li, S You, F Wang, C Qian, Z Lin Advances in Neural Information Processing Systems 33, 10503-10513, 2020 | 64 | 2020 |
| DeMT: Deformable mixer transformer for multi-task learning of dense prediction Y Xu, Y Yang, L Zhang Proceedings of the AAAI conference on artificial intelligence 37 (3), 3072-3080, 2023 | 57* | 2023 |
| Towards improving the consistency, efficiency, and flexibility of differentiable neural architecture search Y Yang, S You, H Li, F Wang, C Qian, Z Lin Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 57 | 2021 |
| Multi-task learning with multi-query transformer for dense prediction Y Xu, X Li, H Yuan, Y Yang, L Zhang IEEE Transactions on Circuits and Systems for Video Technology 34 (2), 1228-1240, 2023 | 54 | 2023 |
| Understanding imbalanced semantic segmentation through neural collapse Z Zhong*, J Cui*, Y Yang*, X Wu, X Qi, X Zhang, J Jia Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 54 | 2023 |
| Panoptic-partformer: Learning a unified model for panoptic part segmentation X Li, S Xu, Y Yang, G Cheng, Y Tong, D Tao European Conference on Computer Vision, 729-747, 2022 | 53 | 2022 |
| Neural collapse inspired attraction–repulsion-balanced loss for imbalanced learning L Xie, Y Yang, D Cai, X He Neurocomputing 527, 60-70, 2023 | 51 | 2023 |
| Optimization algorithm inspired deep neural network structure design H Li*, Y Yang*, D Chen, Z Lin Asian Conference on Machine Learning, 614-629, 2018 | 45 | 2018 |
| Problem-Dependent Power of Quantum Neural Networks on Multiclass Classification Y Du, Y Yang, D Tao, MH Hsieh Physical Review Letters 131 (14), 140601, 2023 | 42* | 2023 |
| Polyphonicformer: unified query learning for depth-aware video panoptic segmentation H Yuan, X Li, Y Yang, G Cheng, J Zhang, Y Tong, L Zhang, D Tao European Conference on Computer Vision, 582-599, 2022 | 41 | 2022 |
Zhouchen LinProfessor, Peking University; Fellow of IEEE, IAPR, CSIG & AAIA; ex-VP of Samsung Research確認したメール アドレス: pku.edu.cn