| SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers E Xie, W Wang, Z Yu, A Anandkumar, JM Alvarez, P Luo Conference on Neural Information Processing Systems (NeurIPS), 2021, 2021 | 4690 | 2021 |
| Sphereface: Deep hypersphere embedding for face recognition W Liu, Y Wen, Z Yu, M Li, B Raj, L Song IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017, 2017 | 3565 | 2017 |
| Large-Margin Softmax Loss for Convolutional Neural Networks. W Liu, Y Wen, Z Yu, M Yang International Conference on Machine Learning (ICML), 2016, 2016 | 1907 | 2016 |
| Domain Adaptation for Semantic Segmentation via Class-Balanced Self-Training Y Zou*, Z Yu*, BVKV Kumar, J Wang European Conference on Computer Vision (ECCV), 2018, 2018 | 1639 | 2018 |
| Joint Discriminative and Generative Learning for Person Re-identification Z Zheng, X Yang, Z Yu, L Zheng, Y Yang, J Kautz IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019, 2019 | 953 | 2019 |
| Confidence Regularized Self-Training Y Zou, Z Yu, X Liu, BVK Kumar, J Wang IEEE/CVF International Conference on Computer Vision (ICCV), 2019, 2019 | 951 | 2019 |
| Image based static facial expression recognition with multiple deep network learning Z Yu, C Zhang ACM International Conference on Multimodal Interaction (ICMI), 2015, 2015 | 741 | 2015 |
| CASENet: Deep category-aware semantic edge detection Z Yu*, C Feng*, MY Liu, S Ramalingam IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017, 2017 | 369 | 2017 |
| Joint Disentangling and Adaptation for Cross-Domain Person Re-Identification Y Zou, X Yang, Z Yu, BVKV Kumar, J Kautz European Conference on Computer Vision (ECCV), 2020, 2020 | 298 | 2020 |
| Constructing the L2-graph for robust subspace learning and subspace clustering X Peng, Z Yu, Z Yi, H Tang IEEE Transactions on Cybernetics 47 (4), 1053-1066, 2017 | 251 | 2017 |
| Test-time prompt tuning for zero-shot generalization in vision-language models M Shu, W Nie, DA Huang, Z Yu, T Goldstein, A Anandkumar, C Xiao Advances in Neural Information Processing Systems 35, 14274-14289, 2022 | 249 | 2022 |
| Instance-Aware, Context-Focused, and Memory-Efficient Weakly Supervised Object Detection Z Ren, Z Yu, X Yang, MY Liu, YJ Lee, AG Schwing, J Kautz IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020, 2020 | 238 | 2020 |
| Uncertainty-aware multi-view co-training for semi-supervised medical image segmentation and domain adaptation Y Xia, D Yang, Z Yu, F Liu, J Cai, L Yu, Z Zhu, D Xu, A Yuille, H Roth Medical Image Analysis (MEDIA), 2020, 2020 | 230 | 2020 |
| Understanding the robustness in vision transformers D Zhou, Z Yu, E Xie, C Xiao, A Anandkumar, J Feng, JM Alvarez International Conference on Machine Learning, 27378-27394, 2022 | 192 | 2022 |
| Voxformer: Sparse voxel transformer for camera-based 3d semantic scene completion Y Li, Z Yu, C Choy, C Xiao, JM Alvarez, S Fidler, C Feng, A Anandkumar Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2023 | 188 | 2023 |
| M2BEV: Multi-Camera Joint 3D Detection and Segmentation with Unified Birds-Eye View Representation E Xie, Z Yu, D Zhou, J Philion, A Anandkumar, S Fidler, P Luo, JM Alvarez arXiv preprint arXiv:2204.05088, 2022 | 179 | 2022 |
| Panoptic SegFormer: Delving deeper into panoptic segmentation with transformers Z Li, W Wang, E Xie, Z Yu, A Anandkumar, JM Alvarez, T Lu, P Luo IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022, 2022 | 172* | 2022 |
| An adaptive unsupervised approach toward pixel clustering and color image segmentation Z Yu, OC Au, R Zou, W Yu, J Tian Pattern recognition 43 (5), 1889-1906, 2010 | 164 | 2010 |
| Learning towards Minimum Hyperspherical Energy W Liu, R Lin, Z Liu, L Liu, Z Yu, B Dai, L Song Conference on Neural Information Processing Systems (NeurIPS), 2018, 2018 | 162 | 2018 |
| Deep Hyperspherical Learning W Liu, YM Zhang, X Li, Z Yu, B Dai, T Zhao, L Song Conference on Neural Information Processing Systems (NIPS), 2017, 2017 | 154 | 2017 |
Anima AnandkumarCalifornia Institute of Technology and NVIDIA在 caltech.edu 的电子邮件经过验证