Adaptive unsupervised multi-view feature selection for visual concept recognition Y Feng, J Xiao, Y Zhuang, X Liu Computer Vision–ACCV 2012: 11th Asian Conference on Computer Vision, Daejeon …, 2013 | 129 | 2013 |
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 | 120 | 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 | 81 | 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 | 76 | 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 | 56 | 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 | 38 | 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 | 37 | 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 | 22 | 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 | 22 | 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 | 15 | 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 |
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 |
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 | 8 | 2016 |
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 |
A human motion feature based on semi-supervised learning of GMM T Qi, Y Feng, J Xiao, H Zhang, Y Zhuang, X Yang, J Zhang Multimedia Systems 23, 85-93, 2017 | 4 | 2017 |
Decomposed Prototype Learning for Few-Shot Scene Graph Generation X Li, L Chen, G Chen, Y Feng, Y Yang, J Xiao arXiv preprint arXiv:2303.10863, 2023 | 2 | 2023 |
A Primal-Dual Online Algorithm for Online Matching Problem in Dynamic Environments AXZ Yu-Hang Zhou, Peng Hu, Chen Liang, Huan Xu, Guangda Huzhang, Yinfu Feng ... AAAI Conference on Artificial Intelligence, 2021 | 2 | 2021 |
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 | 1 | 2023 |