个人简介 :

目前主要从事视觉内容分析与高效计算、机器学习、运筹优化等方面的研究。主持多项国家自然科学基金课题、中科院专项、企业委托项目。在IEEE T-PAMI、IEEE T-IP、IEEE T-CYB、IEEE T-MM等权威国际期刊和NeurIPS、CVPR、ICCV、ECCV、IJCAI等顶级国际会议上发表论文四十余篇。现为中国计算机学会计算机视觉专委会委员，AVS国家标准工作组数字媒体内容描述组组长，IEEE1857.6标准工作组组长。中科院院长奖获得者，中科院青年创新促进会成员，中科院自动化所特聘青年骨干。

发表论文 :

• L. Shi, Y. Zhang, J. Cheng, and H. Lu, "Action recognition via pose-based graph convolutional networks with intermediate dense supervision," Pattern Recognition (PR), Vol. 121, Col. 108170, 2022.
• K. Cheng, Y. Zhang, X. He, J. Cheng, and H. Lu, "Extremely Lightweight Skeleton-Based Action Recognition With ShiftGCN++," IEEE Transactions on Image Processing (T-IP) Vol. 30, pp. 7333-7348, 2021.
• Y. Zhang, L. Shi, Y. Wu, K. Cheng, J. Cheng and H. Lu, "Gesture Recognition Based on Deep Deformable 3D Convolutional Neural Networks," Pattern Recognition (PR), Vol. 107, 2020.
• L. Shi, Y. Zhang, J. Cheng and H. Lu, "Skeleton-Based Action Recognition With Multi-Stream Adaptive Graph Convolutional Networks," IEEE Transactions on Image Processing (T-IP) Vol. 29, pp. 9532-9545, 2020.
• Q. Chen, P. Wang, A. Cheng, W. Wang, Y. Zhang and Jian Cheng, "Robust one-stage object detection with location-aware classifiers.," Pattern Recognition (PR), Vol. 105, Col. 107334, 2020.
• C. Cao, C. Lan, Y. Zhang, W. Zeng, H. Lu and Y. Zhang, "Skeleton-Based Action Recognition With Gated Convolutional Neural Networks," IEEE Transactions on Circuits Systems and Video Technology (T-CSVT), Vol. 29, No. 11, pp. 3247-3257, 2019.
• Y. Zhang, C. Cao, J. Cheng and H. Lu, “EgoGesture: A New Dataset and Benchmark for Egocentric Hand Gesture Recognition,” IEEE Transactions on Multimedia(T-MM), Vol. 20, No. 5, pp. 1038-1050, 2018.
• C. Cao, Y. Zhang, C. Zhang and H. Lu, “Body Joint Guided 3-D Deep Convolutional Descriptors for Action Recognition,” IEEE Transactions on Cybernetics(T-CYB), Vol. 48, No. 3, pp. 1095-1108, 2018.
• Y. Zhang, Z. Tang, B. Wu, Q. Ji, and H. Lu, “A Coupled Hidden Conditional Random Field Model for Simultaneous Face Clustering and Naming in Videos,” IEEE Transactions on Image Processing (T-IP), Vol. 25, No. 12, pp. 5780-5792, 2016.
• Y. Zhang, Y. Zhang, E. Swears, N. Lario, Z. Wang and Q. Ji, “Modeling Temporal Interactions with Interval Temporal Bayesian Networks for Complex Activity Recognition,” IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), Vol. 35, No. 10, pp. 2468-2483, Oct. 2013.
• Y. Zhang, C. Xu, H. Lu and Y. Huang, “Character Identification in Feature-length Films Using Global Face-Name Matching,” IEEE Transactions on Multimedia (T-MM), Vol. 11, No. 7, pp. 1276-1288, 2009.
• C. Xu, Y. Zhang, G. Zhu, Y. Rui, H. Lu and Q. Huang, “Using Web-cast Text for Semantic Event Detection in Broadcast Sports Video,” IEEE Transactions on Multimedia (T-MM), Vol. 10, No. 7, pp. 1342-1355, Nov. 2008.

• Jinmin He, Kai Li, Yifan Zang, Haobo Fu, Qiang Fu, Junliang Xing, Jian Cheng. Not All Tasks Are Equally Difficult: Multi-Task Reinforcement Learning with Dynamic Depth Routing. AAAI 2024.
• Junkai Zhang, Yifan Zhang, Xi Sheryl Zhang, Yifan Zang, Jian Cheng. Intrinsic Action Tendency Consistency for Cooperative Multi-Agent Reinforcement Learning. AAAI 2024.
• Yuheng Jing, Kai Li, Bingyun Liu, Yifan Zang, Haobo Fu, Qiang Fu, Junliang Xing, Jian Cheng. Towards Offline Opponent Modeling with In-context Learning. ICLR 2024.
• Yang Wu, Yifan Zhang, Zhenxing Liang, Jian Cheng. HGCN2SP: Hierarchical Graph Convolutional Network for Two-Stage Stochastic Programming. ICML 2024.
• S. Liu, X. Zhang, Y. Li, Y. Zhang and J. Cheng,"On the Data-Efficiency with Contrastive Image Transformation in Reinforcement Learning," In Proceedings of the Eleventh International Conference on Learning Representations (ICLR),  2023.
• L. Sun, Y. Zhang, J. Cheng and H. Lu,"Asynchronous Event Processing with Local-Shift Graph Convolutional Network,"  In Proceedings of the 37th AAAI Conference on Artificial Intellegence (AAAI), 2023.
• W. Cao, Y. Zhang, J. Gao, A. Cheng, K. Cheng and J. Cheng,"PKD: General Distillation Framework for Object Detectors via Pearson Correlation Coefficient," In Proceedings of Conference on Neural Information Processing Systems (NeurIPS),  2022. (Spotlight)
• L. Sun, Y. Zhang, K. Cheng, J. Cheng and H. Lu,"MENet: a Memory-based network with Dual-branch for Efficient Event Stream Processing," In Proceedings of the European conference on computer vision (ECCV), 2022.
• H. Gao, Y. Zhang, L. Sun and J. Cheng, "Action Representing by Constrained Conditional Mutual Information," In Proceedings of the Asian conference on computer vision (ACCV), 2022.
• L. Shi, Y. Zhang, J. Cheng and H. Lu, "AdaSGN: Adapting Joint Number and Model Size for Efficient Skeleton-Based Action Recognition,"  In Proceedings of IEEE International Conference On Computer Vision (ICCV),  2021.
• K. Cheng, Y. Zhang, C. Cao, L. Shi, J. Cheng and H. Lu, "Decoupling GCN with DropGraph Module for Skeleton-Based Action Recognition, In Proceedings of European Conference on Computer Vision (ECCV), 2020.
• K. Cheng, Y. Zhang, X. He, W. Chen, J. Cheng and H. Lu, "Skeleton-Based Action Recognition with Shift Graph Convolutional Network," in Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, US, 2020. (Oral)
• L. Shi, Y. Zhang, J. Cheng and H. Lu, "Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition," In Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), Long beach, US, 2019.
• L. Shi, Y. Zhang, J. Cheng and H. Lu, "Skeleton-Based Action Recognition with Directed Graph Neural Networks," In Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), Long beach, US, 2019.
• P. Wang, Q. Hu, Y. Zhang, C. Zhang, Y. Liu and J. Cheng, "Two-Step Quantization for Low-bit Neural Networks," in Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, US, 2018.
• Q. Hu, G. Li, P. Wang, Y. Zhang and J Cheng: Training Binary Weight Networks via Semi-Binary Decomposition. In Proceedings of the European conference on computer vision (ECCV), 2018: 657-673.
• C. Cao, Y. Zhang, Y. Wu, H. Lu and J. Cheng, "Egocentric Gesture Recognition Using Recurrent 3D Convolutional Neural Networks with Spatiotemporal Transformer Modules,"  In Proceedings of IEEE International Conference on Computer Vision (ICCV), Venice, Italy, 2017. (Spotlight)
• Q. Hu, J. Wu, L. Bai, Y. Zhang and J. Cheng, "Fast K-means for Large Scale Clustering," In Proceedings of International Conference on Information and Knowledge Management (CIKM) 2017: 2099-2102.
• C. Cao, Y. Zhang, C. Zhang and H. Lu, “Action Recognition with Joints-Pooled 3D Deep Convolutional Descriptors”, In Proceedings of International Joint Conferences on Artificial Intelligence (IJCAI), 2016.
• Z. Tang, Y. Zhang, Z. Li and H. Lu, “Face clustering in videos with proportion prior”, In Proceedings of International Joint Conferences on Artificial Intelligence (IJCAI), Buenos Aires, Argentina, 2015 (Oral).
• C. Cao, Y. Zhang and H. Lu,“Multi-modal learning for gesture recognition”, In Proceedings of IEEE International Conference on Multimedia and Expo (ICME), Torino, Italy, 2015.
• C. Cao, Y. Zhang and H. Lu “Spatio-Temporal Triangular-Chain CRF for Activity Recognition”, In Proceedings of ACM Multimedia 2015: 1151-1154.
• Z. Tang, Y. Zhang, S. Qiu and H. Lu, “Video Face Naming Using Global Sequence Alignment,” In proceedings of IEEE International conference on Image Processing (ICIP), Paris, France, 2014.
• Y. Zhang, Q. Ji and H. Lu, “Event Detection in Complex Scene Using Interval Temporal Constraints,” In Proceedings of IEEE International Conference on Computer Vision (ICCV), pp. 3184-3191, Sydney, Australia, 2013.
• B. Wu，Y. Zhang, B. Hu and Q. Ji, “Constrained Clustering and Its Application to Face Clustering In Videos," In Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), Portland, US, 2013.

获奖情况 :

• 2019年 获得NeurIPS神经网络压缩与加速竞赛ImageNet和CIFAR-100两项任务冠军 
• 2019年 获得ICCV轻量化人脸识别比赛亚军和快速人脸识别比赛亚军 
• 2018年 获得中国图象图形学学会科学技术二等奖 
• 2018年 获得PRCV2018美图短视频实时分类挑战赛冠军
• 2018年 获得“AI Challenger”全球AI挑战赛短视频实时分类比赛亚军 
• 2016年 获得“CCF-腾讯犀牛鸟基金”
• 2014年 入选“中国科学院青年创新促进会”
• 2010年 获得“中国科学院院长优秀奖”

科研项目 :

科技部“新一代人工智能”重大项目子课题，“神经网络表示与压缩标准”，2019.12-2022.12，负责人。

国家自然科学基金，“基于深度时空建模的人体动作识别”，2019.1-2022.12, 负责人。

国家自然科学基金，“基于概率图模型的复杂行为识别”，2016.1-2019.12, 负责人。

国家自然科学基金，“知识与数据混合驱动的概率图模型研究及在行为识别的应用”，2013.1-2015.12, 负责人。

中科院青促会专项， 2014.7-2017.12, 负责人。

中科院院长奖专项，2011.4-2012.12，负责人。

科技部863项目，“网络媒体大数据关联挖掘和多维度呈现”，2014.1-2016.12，课题骨干。