项目简介
国家重点研发计划云计算和大数据重点专项 “面向大范围场景透彻感知的视觉大数据智能分析关键技术与验证系统”项目(2016-2020)于2016年10月正式启动。
通过视觉大数据的深度理解全面掌控大范围复杂场景动态,实现视觉感知不留死角,进而提出了本项目的研究目标:面向大范围场景视觉大数据,突破当前场景范围小、个体识别近、群体刻画弱、事件预警难等“感知盲区”,从“个体-群体-场景”多层次实现大范围复杂场景视觉大数据的多粒度和多维度透彻感知。
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- 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.
- 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.
- Yanbo Fan, Ran He, Jian Liang, and Baogang Hu, “Self-paced learning: an implicit regularization perspective”, Proc. AAAI Conference on Artificial Intelligence, 2017, accepted.
- 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.
- 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).
- 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).
- 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).
- 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)
- 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.
- 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.
- 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.