| Visual saliency based on multiscale deep features G Li, Y Yu Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 1101 | 2015 |
| Deep contrast learning for salient object detection G Li, Y Yu Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 763 | 2016 |
| Visual saliency detection based on multiscale deep CNN features G Li, Y Yu IEEE transactions on image processing 25 (11), 5012-5024, 2016 | 316 | 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 | 266 | 2019 |
| Instance-level salient object segmentation G Li, Y Xie, L Lin, Y Yu Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 252 | 2017 |
| 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 | 221 | 2017 |
| 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 | 183 | 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 | 175 | 2019 |
| 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 | 171 | 2018 |
| Crowd counting using deep recurrent spatial-aware network L Liu, H Wang, G Li, W Ouyang, L Lin arXiv preprint arXiv:1807.00601, 2018 | 158 | 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 | 124 | 2019 |
| 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 | 118 | 2018 |
| 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 | 114 | 2018 |
| 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 | 96 | 2019 |
| Dynamic graph attention for referring expression comprehension S Yang, G Li, Y Yu Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 86 | 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 | 86 | 2019 |
| Semantic relationships guided representation learning for facial action unit recognition G Li, X Zhu, Y Zeng, Q Wang, L Lin Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 8594-8601, 2019 | 76 | 2019 |
| Contrast-oriented deep neural networks for salient object detection G Li, Y Yu IEEE transactions on neural networks and learning systems 29 (12), 6038-6051, 2018 | 72 | 2018 |
| Cross-modal relationship inference for grounding referring expressions S Yang, G Li, Y Yu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 66 | 2019 |
| Weakly supervised salient object detection using image labels G Li, Y Xie, L Lin Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018 | 65 | 2018 |
Liang LinProfessor, School of Computer Science and Engineering, Sun Yat-Sen University, China在 ieee.org 的电子邮件经过验证
