| Visual saliency based on multiscale deep features G Li, Y Yu Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 1561 | 2015 |
| Deep contrast learning for salient object detection G Li, Y Yu Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 933 | 2016 |
| Larger norm more transferable: An adaptive feature norm approach for unsupervised domain adaptation R Xu, G Li, J Yang, L Lin Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 620 | 2019 |
| Visual saliency detection based on multiscale deep CNN features G Li, Y Yu IEEE transactions on image processing 25 (11), 5012-5024, 2016 | 446 | 2016 |
| Multi-label image recognition by recurrently discovering attentional regions Z Wang, T Chen, G Li, R Xu, L Lin Proceedings of the IEEE international conference on computer vision, 464-472, 2017 | 370 | 2017 |
| Instance-level salient object segmentation G Li, Y Xie, L Lin, Y Yu Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 332 | 2017 |
| Crowd counting with deep structured scale integration network L Liu, Z Qiu, G Li, S Liu, W Ouyang, L Lin Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 297 | 2019 |
| Adaptive context selection for polyp segmentation R Zhang, G Li, Z Li, S Cui, D Qian, Y Yu Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 280 | 2020 |
| Non-locally enhanced encoder-decoder network for single image de-raining G Li, X He, W Zhang, H Chang, L Dong, L Lin Proceedings of the 26th ACM international conference on Multimedia, 1056-1064, 2018 | 278 | 2018 |
| Contextualized spatial–temporal network for taxi origin-destination demand prediction L Liu, Z Qiu, G Li, Q Wang, W Ouyang, L Lin IEEE Transactions on Intelligent Transportation Systems 20 (10), 3875-3887, 2019 | 266 | 2019 |
| Attention-aware face hallucination via deep reinforcement learning Q Cao, L Lin, Y Shi, X Liang, G Li Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 244 | 2017 |
| Dynamic graph attention for referring expression comprehension S Yang, G Li, Y Yu Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 236 | 2019 |
| Motion guided attention for video salient object detection H Li, G Chen, G Li, Y Yu Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 230 | 2019 |
| Crowd counting using deep recurrent spatial-aware network L Liu, H Wang, G Li, W Ouyang, L Lin arXiv preprint arXiv:1807.00601, 2018 | 219 | 2018 |
| A real-time cross-modality correlation filtering method for referring expression comprehension Y Liao, S Liu, G Li, F Wang, Y Chen, C Qian, B Li Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 217 | 2020 |
| Referring image segmentation via cross-modal progressive comprehension S Huang, T Hui, S Liu, G Li, Y Wei, J Han, L Liu, B Li Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 205 | 2020 |
| Clusternet: Deep hierarchical cluster network with rigorously rotation-invariant representation for point cloud analysis C Chen, G Li, R Xu, T Chen, M Wang, L Lin Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 203 | 2019 |
| Flow guided recurrent neural encoder for video salient object detection G Li, Y Xie, T Wei, K Wang, L Lin Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 196 | 2018 |
| Recurrent attentional reinforcement learning for multi-label image recognition T Chen, Z Wang, G Li, L Lin Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018 | 185 | 2018 |
| Linguistic structure guided context modeling for referring image segmentation T Hui, S Liu, S Huang, G Li, S Yu, F Zhang, J Han Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 167 | 2020 |
Liang LinFellow of IEEE/IAPR, Research Director of Peng Cheng Laboratory, Professor of Computer Science, SYSU在 ieee.org 的電子郵件地址已通過驗證
