| Ordinal regression with multiple output cnn for age estimation Z Niu, M Zhou, L Wang, X Gao, G Hua IEEE Conference on Computer Vision and Pattern Recognition (CVPR'2016), 4920 …, 2016 | 795 | 2016 |
| SGCN: Sparse Graph Convolution for Pedestrian Trajectory Prediction L Shi, L Wang, C Long, S Zhou, M Zhou, Z Niu, G Hua IEEE/CVF International Conference on Computer Vision and Pattern Recognition …, 2021 | 298* | 2021 |
| Hierarchical Multimodal LSTM for Dense Visual-Semantic Embedding Z Niu, M Zhou, L Wang, X Gao, G Hua IEEE International Conference on Computer Vision (ICCV'2017), 1881-1889, 2017 | 193 | 2017 |
| Two-Stream Consensus Networks for Weakly-Supervised Temporal Action Localization Y Zhai, L Wang, W Tang, Q Zhang, J Yuan, G Hua European Conference on Computer Vision (ECCV'2020), 2020 | 172 | 2020 |
| A Comprehensive Study of Weight Sharing in Graph Networks for 3D Human Pose Estimation K Liu, R Ding, Z Zou, L Wang, W Tang European Conference on Computer Vision (ECCV'2020), 2020 | 170 | 2020 |
| Automatic salient object extraction with contextual cue L Wang, J Xue, N Zheng, G Hua IEEE International Conference on Computer Vision (ICCV'2011), 105-112, 2011 | 157 | 2011 |
| Enriching Local and Global Contexts for Temporal Action Localization Z Zhu, W Tang, L Wang, N Zheng, G Hua IEEE/CVF International Conference on Computer Vision (ICCV'2021), 2021 | 144 | 2021 |
| Weakly Supervised Temporal Action Localization through Contrast based Evaluation Networks Z Liu, L Wang, Q Zhang, W Tang, Z Nanning, G Hua IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI) 44 …, 2022 | 135 | 2022 |
| Video Object Discovery and Co-Segmentation with Extremely Weak Supervision L Wang, G Hua, R Sukthankar, J Xue, Z Niu, N Zheng IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI) 39 …, 2017 | 134 | 2017 |
| MotionTrack: Learning Robust Short-term and Long-term Motions for Multi-Object Tracking Z Qin, S Zhou, L Wang, J Duan, G Hua, W Tang IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR'2023), 2023 | 111 | 2023 |
| Attention-based Temporal Weighted Convolutional Neural Network for Action Recognition J Zang, L Wang, Z Liu, Q Zhang, Z Niu, G Hua, N Zheng International Conference on Artificial Intelligence Applications and …, 2018 | 89 | 2018 |
| ACSNet: Action-Context Separation Network for Weakly Supervised Temporal Action Localization Z Liu, L Wang, Q Zhang, W Tang, J Yuan, N Zheng, G Hua AAAI Conference on Artificial Intelligence (AAAI'2021), 2021 | 83 | 2021 |
| Memory-Augmented Appearance-Motion Network for Video Anomaly Detection L Wang, J Tian, S Zhou, H Shi, G Hua Pattern Recognition (PR) 138, 109335, 2023 | 65 | 2023 |
| Trajectory Unified Transformer for Pedestrian Trajectory Prediction L Shi, L Wang, S Zhou, G Hua IEEE/CVF International Conference on Computer Vision (ICCV'2023), 2023 | 56 | 2023 |
| Learning to Refactor Action and Co-occurrence Features for Temporal Action Localization K Xia, L Wang, S Zhou, N Zheng, W Tang IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR'2022), 2022 | 51 | 2022 |
| Meta Pairwise Relationship Distillation for Unsupervised Person Re-identification H Ji, L Wang, S Zhou, W Tang, N Zheng, G Hua IEEE/CVF International Conference on Computer Vision (ICCV'2021), 2021 | 50 | 2021 |
| Adversarial Ranking Attack and Defense M Zhou, Z Niu, L Wang, Q Zhang, G Hua European Conference on Computer Vision (ECCV'2020), 2020 | 49 | 2020 |
| Compressing unknown images with product quantizer for efficient zero-shot classification J Li, X Lan, Y Liu, L Wang, N Zheng Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 49 | 2019 |
| High-order Graph Convolutional Networks for 3D Human Pose Estimation Z Zou, K Liu, L Wang, W Tang British Machine Vision Conference (BMVC'2020), 2020 | 47 | 2020 |
| Social Interpretable Tree for Pedestrian Trajectory Prediction L Shi, L Wang, C Long, S Zhou, F Zheng, N Zheng, G Hua AAAI Conference on Artificial Intelligence (AAAI'2022), 2022 | 45 | 2022 |
Gang HuaVice President, Multimodal Experiences Research Lab, Dolby Laboratories, IEEE & IAPR Fellow在 dolby.com 的电子邮件经过验证
