| Deep metric learning with hierarchical triplet loss W Ge Proceedings of the European Conference on Computer Vision (ECCV), 269-285, 2018 | 342 | 2018 |
| Borrowing treasures from the wealthy: Deep transfer learning through selective joint finetuning W Ge, Y Yu Proceedings of the IEEE conference on computer …, 2017, 2017 | 237 | 2017 |
| Borrowing treasures from the wealthy: Deep transfer learning through selective joint fine-tuning W Ge arXiv preprint arXiv:1702.08690, 2017 | 234 | 2017 |
| Borrowing Treasures from the Wealthy: Deep Transfer Learning through Selective Joint Fine-tuning W GE, Y YU arXivpreprintarXiv 1702, 08690, 2017 | 234 | 2017 |
| Weakly supervised complementary parts models for fine-grained image classification from the bottom up W Ge, X Lin, Y Yu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 219 | 2019 |
| Multi-evidence Filtering and Fusion for Multi-Label Classification, Object Detection and Semantic Segmentation Based on Weakly Supervised Learning W Ge, S Yang, Y Yu CVPR, 2018 | 212 | 2018 |
| Multi-evidence filtering and fusion for multi-label classification, object detection and semantic segmentation based on weakly supervised learning W Ge, S Yang, Y Yu Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 211 | 2018 |
| A systematic review on affective computing: Emotion models, databases, and recent advances Y Wang, W Song, W Tao, A Liotta, D Yang, X Li, S Gao, Y Sun, W Ge, ... Information Fusion, 2022 | 68 | 2022 |
| Label-penet: Sequential label propagation and enhancement networks for weakly supervised instance segmentation W Ge, S Guo, W Huang, MR Scott Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 39 | 2019 |
| GraphFPN: Graph feature pyramid network for object detection G Zhao, W Ge, Y Yu Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 38 | 2021 |
| Dynamic background estimation and complementary learning for pixel-wise foreground/background segmentation W Ge, Z Guo, Y Dong, Y Chen Pattern Recognition 59, 112-125, 2016 | 34 | 2016 |
| Multi-scale matching networks for semantic correspondence D Zhao, Z Song, Z Ji, G Zhao, W Ge, Y Yu Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 24 | 2021 |
| Weakly Supervised Image Segmentation Via Curriculum Learning W Ge, S Guo, W Huang, MR Scott US Patent App. 16/525,309, 2021 | 22 | 2021 |
| Attribute surrogates learning and spectral tokens pooling in transformers for few-shot learning Y He, W Liang, D Zhao, HY Zhou, W Ge, Y Yu, W Zhang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 18 | 2022 |
| Ferv39k: a large-scale multi-scene dataset for facial expression recognition in videos Y Wang, Y Sun, Y Huang, Z Liu, S Gao, W Zhang, W Ge, W Zhang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 16 | 2022 |
| Image super-resolution via deterministic-stochastic synthesis and local statistical rectification W Ge, B Gong, Y Yu ACM Transactions on Graphics (TOG) 37 (6), 1-14, 2018 | 14 | 2018 |
| Background subtraction with dynamic noise sampling and complementary learning W Ge, Y Dong, Z Guo, Y Chen 2014 22nd International Conference on Pattern Recognition, 2341-2346, 2014 | 8 | 2014 |
| DPCNet: Dual Path Multi-Excitation Collaborative Network for Facial Expression Representation Learning in Videos Y Wang, Y Sun, W Song, S Gao, Y Huang, Z Chen, W Ge, W Zhang Proceedings of the 30th ACM International Conference on Multimedia, 101-110, 2022 | 3 | 2022 |
| MISC210K: A Large-Scale Dataset for Multi-Instance Semantic Correspondence Y Sun, Y Huang, H Guo, Y Zhao, R Wu, Y Yu, W Ge, W Zhang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | | 2023 |
| Correspondence Transformers With Asymmetric Feature Learning and Matching Flow Super-Resolution Y Sun, D Zhao, Z Yin, Y Huang, T Gui, W Zhang, W Ge Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | | 2023 |
Yizhou YuThe University of Hong Kong, ACM Fellow & IEEE Fellow在 acm.org 的电子邮件经过验证
