张一帆 研究员 博导 中国科学院自动化研究所
电子邮件: yfzhang@nlpr.ia.ac.cn
通信地址: 北京市海淀区中关村东路95号
邮政编码: 100190
个人主页:http://www.nlpr.ia.ac.cn/iva/yfzhang/index.html
目前主要从事视觉内容分析与高效计算、机器学习、智能决策等方面的研究。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、ICML等顶级国际会议上发表论文五十余篇。中国计算机学会计算机视觉专委会委员,中国图象图形学学会机器视觉专委会委员,AVS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,中科院特聘研究骨干。
研究领域
机器学习(包括深度学习、强化学习、概率图模型等)
视觉内容分析与高效计算、人体行为识别
智能决策、机器学习驱动的组合优化
招生信息
招生专业
招生方向
招生要求
专业背景不限。但希望你对科研怀有强烈的兴趣和追求卓越的精神,具备良好的数学基础、编程能力以及自主学习能力。
由于招生数量有限,希望提前与我联系。
另招收少量实习生,要求计算机相关专业的在读本科或研究生,具有较强的编程能力,实习期半年以上者优先。
教育背景
工作经历
工作简历
2020.10~至今,中国科学院自动化研究所 模式识别国家重点实验室, 研究员
2014.10~2020.09,中国科学院自动化研究所 模式识别国家重点实验室, 副研究员
2011.05~2012.07,美国伦斯勒理工学院(RPI) 电子计算机工程系, 博士后
2010.06~2014.09,中国科学院自动化研究所 模式识别国家重点实验室, 助理研究员
社会兼职
2017.02~至今,AVS国家标准工作组数字媒体内容描述组组长
2015.12~至今,IEEE1857.6标准工作组组长
荣誉与奖励
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”
出版信息
期刊论文:
- Transactions on Circuits Systems and Video Technology (T-CSVT), Vol. 33, No. 2, pp. 963-976, 2023. Y. Lu, C. Cao Y. Zhang, and Y. Zhang,"Learnable Locality-Sensitive Hashing for Video Anomaly Detection" IEEE
- 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.
- (T-IP) Vol. 30, pp. 7333-7348, 2021. K. Cheng, Y. Zhang, X. He, J. Cheng, and H. Lu, "Extremely Lightweight Skeleton-Based Action Recognition With ShiftGCN++," IEEE Transactions on Image Processing
- 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.
会议论文:
- Y. Wu, Y. Zhang, Z. Liang and J. Cheng, "HGCN2SP: Hierarchical Graph Convolutional Network for Two-Stage Stochastic Programming," I41st International Conference on Machine Learning n Proceedings of the (ICML), 2024.
- J. Zhang, Y. Zhang, X. Zhang, Y. Zang and J. Cheng, "Intrinsic Action Tendency Consistency for Cooperative Multi-Agent Reinforcement Learning," In Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI), 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 Intelligence (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.
- In Proceedings of the Asian conference on computer vision (ACCV), 2022. H. Gao, Y. Zhang, L. Sun and J. Cheng, "Action Representing by Constrained Conditional Mutual Information,"
- 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.
科研活动
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。