代表性论文
1.Lifang Wu, Meng Tian, Ye Xiang, Ke Gu, Ge Shi. Learning label semantics for weakly supervised group activity recognition. IEEE Transactions on Multimedia, 26: 6386-6397, 2024.(JCR Q1)
2.Zhuming Wang, Zun Li, Xianglong Lang, Yihao Zheng, Meng Tian,Lifang Wu#, Liang Wang, Changwen Chen. Knowledge Augmented Relation Inference for Group Activity Recognition. IEEE Transactions on Circuits and Systems for Video Technology, 34(11): 1164.4-11656, 2024.(JCR Q1)
3.Zhao LD, Zhao Z, Ma LM, Men ZN, Ma YK,Wu LF#. Limiting defect in vat photopolymerization via visual-guided in-situ repair[J]. Additive Manufacturing, 2024, 79: 103947.(JCR Q1)
4.Yongluo Liu, Zun Li, Yaowen Xu, Zhizhi Guo, Zhaofan Zou,Lifang Wu#. Quality-Invariant Domain Generalization for Face Anti-Spoofing. Int. J. Comput. Vis. 132(11): 5239-5254 (2024)(JCR Q1)
5.Shuyi Li, Ruijun Ma, Jianhang Zhou, Bob Zhang and Lifang Wu#. Joint Discriminative Analysis with Low-Rank Projection for Finger Vein Feature Extraction [J]. IEEE Transactions on Information Forensics and Security, 19, 959-969, 2024. (JCR Q1)
6.Jian Meng, Guo Jingjing, Zhang Chenlin, Jia Ting,Wu Lifang#. Yang Xun, Huo Lina. Semantic manifold modularization-based ranking for image recommendation,Pattern Recognition, vol.120, pp. 108100, 2021.(JCR Q1)
7.Deng Sinuo,Wu Lifang, Shi Ge#. Simple but Powerful, a Language-Supervised Method for Image Emotion Classification.IEEE Transactions on Affective Computing,2022.DOI:10.1109/TAFFC.2022.3225049(JCR Q1)
8.Wu Lifang, Yang Zhou, Jian Meng#, Shen Jialie, Yang Yuchen, Lang Xianglong.Global motion estimation with iterative optimization-based independent univariate model for action recognition,Pattern Recognition, vol.116, pp. 107925, 2021.(JCR Q1)
9.Yuchen Yang, Ye Xiang, Shuaicheng Liu,Lifang Wu#, Boxuan Zhao, and Bing Zeng. GLM-Net: Global and Local Motion Estimation via Task-Oriented Encoder-Decoder Structure.ACM International Conference on Multimedia. pp.4211-4219, 2021. (CCF A类会议)
10.Zhuming Wang, Yaowen Xu,Lifang Wu#, Hu Han, Yukun Ma and Guozhang Ma. Multi-Perspective Features Learning for Face Anti-Spoofing[C]. 2021IEEE/CVF International Conference on Human Centered Computer Vision Workshops, 2021: 4099-4105 (Best Paper)