| Learning from noisy labels with distillation Y Li, J Yang, Y Song, L Cao, J Luo, LJ Li Proceedings of the IEEE International Conference on Computer Vision, 1910-1918, 2017 | 651 | 2017 |
| Asynchronous parallel stochastic gradient for nonconvex optimization X Lian, Y Huang, Y Li, J Liu Advances in Neural Information Processing Systems, 2737-2745, 2015 | 546 | 2015 |
| 3D Hand Shape and Pose Estimation from a Single RGB Image L Ge, Z Ren, Y Li, Z Xue, Y Wang, J Cai, J Yuan Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019 | 493 | 2019 |
| TGIF: A new dataset and benchmark on animated GIF description Y Li, Y Song, L Cao, J Tetreault, L Goldberg, A Jaimes, J Luo Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016 | 277 | 2016 |
| Improving pairwise ranking for multi-label image classification Y Li, Y Song, J Luo Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 260 | 2017 |
| Mining fashion outfit composition using an end-to-end deep learning approach on set data Y Li, L Cao, J Zhu, J Luo IEEE Transactions on Multimedia 19 (8), 1946-1955, 2017 | 222 | 2017 |
| Action recognition with spatio–temporal visual attention on skeleton image sequences Z Yang, Y Li, J Yang, J Luo IEEE Transactions on Circuits and Systems for Video Technology 29 (8), 2405-2415, 2018 | 182 | 2018 |
| Learning effective gait features using LSTM Y Feng, Y Li, J Luo 2016 23rd International Conference on Pattern Recognition (ICPR), 325-330, 2016 | 160 | 2016 |
| Using user generated online photos to estimate and monitor air pollution in major cities Y Li, J Huang, J Luo Proceedings of the 7th International Conference on Internet Multimedia …, 2015 | 94 | 2015 |
| Multi-modal deep feature learning for RGB-D object detection X Xu, Y Li, G Wu, J Luo Pattern Recognition 72, 300-313, 2017 | 92 | 2017 |
| Temporal Structure Mining for Weakly Supervised Action Detection T Yu, Z Ren, Y Li, E Yan, N Xu, J Yuan Proceedings of the IEEE International Conference on Computer Vision, 5522-5531, 2019 | 91 | 2019 |
| Deciphering the 2016 US Presidential campaign in the Twitter sphere: A comparison of the Trumpists and Clintonists Y Wang, Y Li, J Luo Tenth International AAAI Conference on Web and Social Media, 2016 | 88 | 2016 |
| Skin disease classification versus skin lesion characterization: Achieving robust diagnosis using multi-label deep neural networks H Liao, Y Li, J Luo 2016 23rd International Conference on Pattern Recognition (ICPR), 355-360, 2016 | 77 | 2016 |
| Catching fire via" likes": Inferring topic preferences of trump followers on twitter Y Wang, J Luo, R Niemi, Y Li, T Hu Tenth International AAAI Conference on Web and Social Media, 2016 | 76 | 2016 |
| Dynamic Kernel Distillation for Efficient Pose Estimation in Videos X Nie, Y Li, L Luo, N Zhang, J Feng Proceedings of the IEEE International Conference on Computer Vision, 6942-6950, 2019 | 71 | 2019 |
| Adaptive greedy dictionary selection for web media summarization Y Cong, J Liu, G Sun, Q You, Y Li, J Luo IEEE Transactions on Image Processing 26 (1), 185-195, 2016 | 62 | 2016 |
| Laplace landmark localization JP Robinson, Y Li, N Zhang, Y Fu, S Tulyakov Proceedings of the IEEE International Conference on Computer Vision, 10103-10112, 2019 | 52 | 2019 |
| A markov logic framework for recognizing complex events from multimodal data YC Song, H Kautz, J Allen, M Swift, Y Li, J Luo, C Zhang Proceedings of the 15th ACM on International conference on multimodal …, 2013 | 41 | 2013 |
| Pinterest board recommendation for twitter users X Yang, Y Li, J Luo Proceedings of the 23rd ACM international conference on Multimedia, 963-966, 2015 | 35 | 2015 |
| To follow or not to follow: Analyzing the growth patterns of the trumpists on Twitter Y Wang, J Luo, R Niemi, Y Li Tenth International AAAI Conference on Web and Social Media, 2016 | 32 | 2016 |
Jiebo LuoAlbert Arendt Hopeman Professor of Engineering, University of Rochester在 cs.rochester.edu 的电子邮件经过验证
