| Adaptive unsupervised multi-view feature selection for visual concept recognition Y Feng, J Xiao, Y Zhuang, X Liu Asian conference on computer vision, 343-357, 2012 | 140 | 2012 |
| Feature correlation hypergraph: exploiting high-order potentials for multimodal recognition L Zhang, Y Gao, C Hong, Y Feng, J Zhu, D Cai IEEE transactions on cybernetics 44 (8), 1408-1419, 2013 | 123 | 2013 |
| Adaptive multi-view feature selection for human motion retrieval Z Wang, Y Feng, T Qi, X Yang, JJ Zhang Signal Processing 120, 691-701, 2016 | 87 | 2016 |
| Exploiting temporal stability and low-rank structure for motion capture data refinement Y Feng, J Xiao, Y Zhuang, X Yang, JJ Zhang, R Song Information Sciences 277, 777-793, 2014 | 83 | 2014 |
| Mining spatial-temporal patterns and structural sparsity for human motion data denoising Y Feng, M Ji, J Xiao, X Yang, JJ Zhang, Y Zhuang, X Li IEEE transactions on cybernetics 45 (12), 2693-2706, 2014 | 58 | 2014 |
| Sparse motion bases selection for human motion denoising J Xiao, Y Feng, M Ji, X Yang, JJ Zhang, Y Zhuang Signal Processing 110, 108-122, 2015 | 42 | 2015 |
| Predicting missing markers in human motion capture using l1‐sparse representation J Xiao, Y Feng, W Hu Computer Animation and Virtual Worlds 22 (2‐3), 221-228, 2011 | 39 | 2011 |
| A semantic feature for human motion retrieval T Qi, Y Feng, J Xiao, Y Zhuang, X Yang, J Zhang Computer animation and virtual worlds 24 (3-4), 399-407, 2013 | 28 | 2013 |
| A locally weighted sparse graph regularized non-negative matrix factorization method Y Feng, J Xiao, K Zhou, Y Zhuang Neurocomputing 169, 68-76, 2015 | 23 | 2015 |
| Sketch-based human motion retrieval via selected 2D geometric posture descriptor J Xiao, Z Tang, Y Feng, Z Xiao Signal Processing 113, 1-8, 2015 | 23 | 2015 |
| A 3D human motion refinement method based on sparse motion bases selection Z Wang, Y Feng, S Liu, J Xiao, X Yang, JJ Zhang Proceedings of the 29th international conference on computer animation and …, 2016 | 17 | 2016 |
| Active learning for social image retrieval using Locally Regressive Optimal Design Y Feng, J Xiao, Z Zha, H Zhang, Y Yang Neurocomputing 95, 54-59, 2012 | 11 | 2012 |
| Fast view-based 3D model retrieval via unsupervised multiple feature fusion and online projection learning J Xiao, Y Feng, M Ji, Y Zhuang Signal Processing 120, 702-713, 2016 | 10 | 2016 |
| Efficient semi-supervised multiple feature fusion with out-of-sample extension for 3D model retrieval M Ji, Y Feng, J Xiao, Y Zhuang, X Yang, JJ Zhang Neurocomputing 169, 23-33, 2015 | 10 | 2015 |
| Real‐time motion data annotation via action string T Qi, J Xiao, Y Zhuang, H Zhang, X Yang, J Zhang, Y Feng Computer Animation and Virtual Worlds 25 (3-4), 291-300, 2014 | 8 | 2014 |
| Human motion retrieval based on freehand sketch Z Tang, J Xiao, Y Feng, X Yang, J Zhang Computer Animation and Virtual Worlds 25 (3-4), 271-279, 2014 | 7 | 2014 |
| Decomposed prototype learning for few-shot scene graph generation X Li, J Xiao, G Chen, Y Feng, Y Yang, AA Liu, L Chen ACM Transactions on Multimedia Computing, Communications and Applications 21 …, 2024 | 6 | 2024 |
| UHD aerial photograph categorization by leveraging deep multiattribute matrix factorization L Zhang, G Wang, Z Wang, Y Feng, B Tu IEEE Transactions on Geoscience and Remote Sensing 61, 1-12, 2023 | 6 | 2023 |
| Multi-domain deep learning from a multi-view perspective for cross-border e-commerce search Y Zhang, Y Feng, WJ Zhou, Y Ye, M Tan, R Xiao, H Tang, J Ding, J Yu Proceedings of the AAAI Conference on Artificial Intelligence 38 (8), 9387-9395, 2024 | 5 | 2024 |
| Fedsea: Federated learning via selective feature alignment for non-iid multimodal data M Tan, Y Feng, L Chu, J Shi, R Xiao, H Tang, J Yu IEEE Transactions on Multimedia 26, 5807-5822, 2023 | 5 | 2023 |
Jun XIAO （肖俊）Institute of Artificial Intelligence, Zhejiang UniversityZweryfikowany adres z zju.edu.cn