论文

2016

• Junlin Hu, Jiwen Lu, Yap-Peng Tan, and Jie Zhou, “Deep transfer metric learning,” IEEE Trans. on Image Processing (TIP), vol.25, no. 12, pp. 5576-5588, 2016.
• Renliang Weng, Jiwen Lu, Yap-Peng Tan, and Jie Zhou, “Learning cascaded deep auto-encoder networks for face alignment, IEEE Trans. On Multimedia (TMM), vol.18, no. 10, pp. 2066-2078, 2016.
• Zifeng Wu, Yongzhen Huang, Liang Wang, Xiaogang Wang, and Tieniu Tan, A comprehensive study on cross-view gait based human identification with deep CNNs, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2016.
• Fang Zhao, Yongzhen Huang, Liang Wang, Tao Xiang, Tieniu Tan, Learning Relevance Restricted Boltzmann Machine for Un-structured Group Activity and Event Understanding, IJCV,119(3):329-345,2016.
• Fang Zhao, Yongzhen Huang, Liang Wang, Tao Xiang, Tieniu Tan, Learning Relevance Restricted Boltzmann Machine for Un-structured Group Activity and Event Understanding, IJCV,119(3):329-345,2016.
• Fang Zhao, Yongzhen Huang, Liang Wang, Tao Xiang, Tieniu Tan, Learning Relevance Restricted Boltzmann Machine for Un-structured Group Activity and Event Understanding, IJCV,119(3):329-345,2016.
• Yong Du, Yun Fu, Liang Wang, Representation Learning of Temporal Dynamics for Skeleton-Based Action Recognition. IEEE Trans. Image Processing 25(7): 3010-3022 (2016).
• J. Qin, Y. Wang, L. Liu, J. Chen and L. Shao, Beyond Semantic Attributes: Discrete Latent Attributes Learning for Zero-Shot Recognition, IEEE Signal Processing Letters (SPL), vol. 23, no. 11, pp. 1667-1671, Nov. 2016.
• Jie Gui, Zhenan Sun, Shuiwang Ji, Dacheng Tao, Tieniu Tan, Feature Selection Based on Structured Sparsity: A Comprehensive Study, IEEE Transactions on Neural Networks and Learning Systems, 2016, published online.
• Y. Sun, K. Nasrollahi, Z. Sun, T. Tan, "Complementary Cohort Strategy for Multimodal Face Pair Matching", IEEE Transactions on Information Forensics and Security, Vol.11, No.5, 2016, pp.937-950.
• Chao Ma, Yi Xu, Bingbing Ni, and Xiaokang Yang, "When Correlation Filters Meet Convolutional Neural Networks for Visual Tracking," IEEE Signal Processing Letters, 2016.
• Chao Ma, Chih-Yuan Yang, Xiaokang Yang, and Ming-Hsuan Yang, "Learninga No-reference Quality Metric for Single-Image Super-Resolution, "Computer Vision and Image Understanding, 2016, published online.
• Xiongkuo Min, Guangtao Zhai, Ke Gu, Yuming Fang, Xiaokang Yang,Xiaolin Wu, Jiantao Zhou, Xiaoming Liu. Blind Quality Assessment ofCompressed Images via Pseudo Structural Similarity ， InternationalConference on Media and Expo, 2016.(最佳论文奖)
• Yichao Yan, Bingbing Ni, Zhichao Song, Chao Ma, Yan Yan, and XiaokangYang, "Person Re-Identification via Recurrent Feature Aggregation," inEuropean Conference on Computer Vision, 2016.

2017

• Yanbo Fan, Ran He, Jian Liang, and Baogang Hu, “Self-paced learning: an implicit regularization perspective”, Proc. AAAI Conference on Artificial Intelligence, 2017, accepted.
• Ran He, Xiang Wu, Zhenan Sun, and Tieniu Tan, “Learning invariant deep representation for NIR-VIS face recognition”, Proc.AAAI Conference on Artificial Intelligence, 2017, accepted.
• JianFang Hu, Wei-Shi Zheng, Jianhuang Lai, and Jianguo Zhang, Jointly Learning Heterogeneous Features for RGB-D Activity Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2017 (DOI:10.1109/TPAMI.2016.2640292).
• Jiazhi He, Jianfang Hu, Xi Lu, Wei-Shi Zheng, Multi-Task Mid-Level Feature Learning for Micro-Expression Recognition. Pattern Recognition, 2017 (DOI: 10.1016/j.patcog.2016.11.029).
• Zhe Ren, Junchi Yan, Bingbing Ni, Bin Liu, Xiaokang Yang and HongyuanZha. Unsupervised deep learning for optical flow estimation, TheThirty-First AAAI Conference on Artificial Intelligence, 2017.
• Le Wang, Gang Hua, Rahul Sukthankar, Jianru Xue, Zhenxing Niu, Nanning Zheng “Video Object and Co-Segmentation with Extremly Weak Supervision”, IEEE Transactions on Pattern Analysis and Machine Intelligence, in Press.
• Dongyu Zhang, Liang Lin*, Tianshui Chen, Xian Wu, Wenwei Tan, and Ebroul Izquierdo, "Content-Adaptive Sketch Portrait Generation by Decompositional Representation Learning", IEEE Transactions on Image Processing (T-IP), 26(1):328-339, 2017
• Chenglong Li, Liang Lin*, Wangmeng Zuo, and Jin Tang, "Learning Patch-based Dynamic Graph for Visual Tracking", Proc. of AAAI Conference on Artificial Intelligence (AAAI), February 2017, USA.

专利

2016

• 郭振华、沈元、陈友斌，一种行人实时检测与跟踪方法，申请号：201611103684.3，申请日期：2016.12.05
• “适于虚拟现实设备的人机交互与身份认证装置及其方法”，中科虹霸，申请号：2016107299615
• “支持头戴模式人机交互与身份认证的虚拟现实设备”，中科虹霸，申请号：201620900870.9
• 孙哲南、赫然、谭铁牛、宋凌霄、曹冬、李琦，基于多任务神经网络的人脸检索方法，专利申请号：201611242736.5，申请日期：2016年12月29日
• 孙哲南，曹冬，李琦，谭铁牛，基于深度学习的室内定位方法专利，专利申请号：201611242717.2，申请日期：2016年12月29日
• 孙哲南，曹冬，李琦，谭铁牛，一种基于深度学习的智能行车驾驶员疲劳预警系统，专利申请号：201611242738.4，申请日期：2016年12月29日

2017

• “人体骨架运动序列行为识别方法”，王亮，杜勇，申请号：201610562181.6，申请日：2016年7月15日