陈杰（教授）查看源代码讨论查看历史
 |
陈杰，男，北京大学信息工程学院副教授。
人物简历
博士毕业于哈尔滨工业大学，先后在芬兰奥卢大学，美国马里兰大学和杜克大学工作。
研究方向
1、深度学习； 2、计算机视觉与模式识别； 3、医学图像分析；4、自然语言处理；5、AI4Science。
科研项目
- 国家科技部 鹏城云脑网络智能重大科技基础设施 ， PCL2021A13，2021-06至 2023-6， 2165.14 万，在研，课题负责人
- 深圳市发改委，大规模医疗健康仿真系统，4339.50万元，鹏城实验室云脑II平台软件，实验室团队项目负责人
- 国家自然科学基金，61972217, 小样本复杂场景图像的结构解析与学习, 2020/1/1—2023/12/31
- 广东省联合基金重点项目，2019B1515120049, 大规模图像数据库增量计算理论与系统，2020/1/1—2022/12/31
- 广东省防控新型冠状病毒感染科技攻关应急专项，2020B1111340056，小样本新型冠状肺炎的多模态可解释性早期诊断，2020-2至2021-6，800万
- 深圳市政府资助，医学大数据库收集与医学图像分析，2018/6/1-2020/12/31
- 国家自然科学基金, 61671427, 弱监督视觉目标检测, 2017/1/1—2020/12/31
- University of Oulu, Finland, Heart ratio measurement from VIS lighting conditions, 2015/3/1-2015/4/31
- 国家自然科学基金, 61271433, 多视角多姿态人体目标检测, 2013/1/1-2016/12/31
- University of Oulu, Finland, Local descriptor for face recognition, 2012/9/1-2012/11/31
- Academy of Finland, Affective human-robot interaction, 01/2009 - 12/2018
- Finland Tekes, Joint Research in Face Analysis and Visual Surveillance (JointFavis), 04/2008 - 03/2010
- Academy of Finland, Texture analysis in machine vision, 09/2007- 12/2018
学术荣誉
中国第一届生物测定学竞赛（BVC2004）人脸验证竞赛第一名
IAPR ICB 2006 人脸验证竞赛第一名，该竞赛由英国University of Surrey的Josef Kittler 组织。
2005年国家科技进步二等奖，获奖项目：人脸识别理论、技术、系统及其应用
2015年国家科技进步二等奖，获奖项目：视觉模式的局部建模及非线性特征获取理论与方法研究
学术成果
论文
署名作者文章100+篇，包括Nature 子刊，TPAMI，IJCV，TIP，CVPR，ICCV，ECCV，NIPS等。根据Google Scholar 统计，到2022年8月初为止，文献被引用次数达6,500+次。详细的论文列表见链接：
刊物
[1] J. Chen, S. Shan, C. He, G. Zhao, M. Pietikäinen, X. Chen, and W. Gao. WLD: A Robust Local Image Descriptor. IEEE Trans. on Pattern Analysis and Machine Intelligence. 32(9):1705-1720, 2010 (SCI: 24)（引用排名在AI领域从2010到2014的五年内的所有文献中排名第56，数据是基于WoS Core的统计）（TPAMI）（国际顶级期刊）（引用1200余次）
[2] Xiawu Zheng, Rongrong Ji, Qiang Wang, Yuhang Chen, Baochang, Zhang, Jie Chen, Qixiang Ye, Feiyue Huang, Yonghong Tian, MIGO-NAS: Towards Fast and Generalizable Neural Architecture Search, IEEE Trans. on Pattern Analysis and Machine Intelligence. (已录用) (SCI: 24) （TPAMI）（国际顶级期刊）
[3] M. Pietikainen, L. Liu, J. Chen, X. Wang, G. Zhao, R. Chellappa, Compact and Efficient Feature Representation and Learning in Computer Vision, Editorial for a special issue on IEEE Trans. on Pattern Analysis and Machine Intelligence, 2018 (SCI: 24) （TPAMI）
[4] R. Wang, S. Shan, X. Chen, J. Chen, and W. Gao. Maximal Linear Embedding for Dimensionality Reduction. IEEE Trans. on Pattern Analysis and Machine Intelligence. 33(9):1776-1792, 2011 (72 citations by Google Scholar) (SCI: 24) （TPAMI）（国际顶级期刊）
[5] L. Liu, W. Ouyang, X. Wang, P. Fieguth, J. Chen, X.Liu, M. Pietikainen, Deep Learning for Generic Object Detection: A Survey, International Journal of Computer Vision（IJCV）2020, (SCI: 13)（1700+ citations by Google Scholar）
[6] L. Liu, J. Chen, P. Fieguth, G. Zhao, R. Chellappa, M. Pietikainen, From BoW to CNN: Two Decades of Texture Representation for Texture Classification, International Journal of Computer Vision 2019 (IJCV) (SCI: 13)
[7] J. Chen, R. Wang, S. Yan, S. Shan, X. Chen, and W. Gao. Enhancing Human Face Detection by Resampling Examples through Manifolds. IEEE Trans. on System Man, and Cybernetics. 37(6):1017-1028, 2007.11 (39 citations by Google Scholar) (SCI: 13) (TSMC) （国际顶级期刊）
[8] W. Ke, J. Chen, J. Jiao, G. Zhao, Q. Ye, SRN: Side-output Residual Network for Object Symmetry Detection in the Wild, IEEE Transactions on Neural Networks and Learning Systems, 2018 (SCI: 14) （TNNLS）
[9] Ce Li, Chunyu Xie, Baochang Zhang, Jungong Han, Xiantong Zhen, Jie Chen; "Memory Attention Networks for Skeleton-based Action Recognition, IEEE Transactions on Neural Networks and Learning Systems 2021, (SCI: 14) （TNNLS）
[10] J. Chen, G. Zhao, M. Salo, E. Rahtu, and M. Pietikäinen, Automatic Dynamic Texture Segmentation Using Local Descriptors and Optical Flow, IEEE Trans. on Image Processing, 2013 (73 citations by Google Scholar) (SCI: 11) （TIP）（国际顶级期刊）
[11] S. Xie, S. Shan, X. Chen, and J. Chen, Fusing Local Patterns of Gabor Magnitude and Phase for Face Recognition, IEEE Trans. on Image Processing, 19(5), pp: 1349-1361, 2010, (430 citations by Google Scholar) (SCI: 11) （引用排名在AI领域从2010到2014五年内的所有文献中排名第225，数据是基于WoS Core的统计）(TIP) （国际顶级期刊）
[12] L. Liu, J. Chen, G. Zhao, P. Fieguth, X. Chen, M. Pietikäinen, Texture Classification in Extreme Scale Variations using GANet, IEEE Trans. Image Processing, (SCI: 11) (TIP) （国际顶级期刊）
[13] Q. Liu, X. Hong, B. Zou, J. Chen, Z. Chen, Hierarchical Contour Closure based Holistic Salient Object Detection, IEEE Transactions on Image Processing, 2017 (SCI: 11) (TIP) （国际顶级期刊）
[14] Y. Xu, X. Hong, J. Chen, X. Liu, F. Porikli, G. Zhao, Saliency Integration: An Arbitrator Model, IEEE Transactions on Multimedia, 2019 (SCI: 8.1)（TMM）（国际顶级期刊）
[15] Jiancheng Cai, Han Hu, Jiyun Cui, Jie Chen, Li Liu, S.Kevin Zhou; Semi-supervised Natural Face De-occlusion IEEE Transactions on Information Forensics & Security (SCI: 7.2) (TIFS), 2020（国际顶级期刊）
[16] J. Chen, X. Chen, J. Yang, S. Shan, R. Wang, and W. Gao, Optimization of a training set for more robust face detection, Pattern recognition, 41(11):2828-2840, 2009 (43 citations by Google Scholar) (SCI: 8.5) (PR) （国际顶级期刊）
[17] X. Qi, G. Zhao, J. Chen, M. Pietikäinen, Exploring Illumination Robust Descriptors for Human Epithelial Type 2 Cell Classification, Pattern Recognition, 2016 (SCI: 8.5) (PR) （国际顶级期刊）
[18] Huang, Lun; Wang, Wenmin; Xia, Yaxian; Chen, Jie; ", Adaptively aligned image captioning via adaptive attention time, Advances in Neural Information Processing Systems （NIPS），2019 （国际顶级会议）
[19] Lun Huang, Wenmin Wang, Jie Chen and Xiao-Yong Wei, Attention on Attention for Image Captioning. In IEEE International Conference on Computer Vision (ICCV), 2019. (Oral) （国际顶级会议）(400+citations by Google Scholar)
[20] Can Zhang，Meng Cao，Dongming Yang，Jie Chen，Yuexian Zou; " Learn to Compare: Localize Actions under Weak Supervision, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)，2021 （国际顶级会议）
[21] Qiong Wu, Pingyang Dai, Jie Chen, Chia-Wen Lin, Yongjian Wu, Feiyue Huang, Bineng Zhong, Rongrong Ji; Discover Cross-Modality Nuances for Visible-Infrared Person Re-Identification，Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021 （国际顶级会议）
[22] Y. Zhai, S. Lu, Q. Ye, X. Shan, J. Chen, R. Ji，Y. Tian，AD-Cluster: Augmented Discriminative Clustering for Domain Adaptive Person Re-identification，The Conference on Computer Vision and Pattern Recognition (CVPR，Google 统计计算机视觉&模式 识别领域影响力最高的刊物) 2020 （国际顶级会议）
[23] Q. Ye, T. Zhang, Q. Qiu, B. Zhang, J. Chen, and G. Sapiro, Self-learning Scene-specific Pedestrian Detectors using a Progressive Latent Model, IEEE International Conference on Computer Vision and Pattern Recognition, 2017 (CVPR) （国际顶级会议）
[24] W. Ke, J. Chen, J. Jiao, G. Zhao, Q. Ye, SRN: Side-output Residual Network for Object Symmetry Detection in the Wild, IEEE International Conference on Computer Vision and Pattern Recognition, 2017 (Oral, 1.72% 录用率) (CVPR) （国际顶级会议）
[25] X. Li, J. Chen, G. Zhao and M. Pietikäinen, Remote heart rate measurement from face videos under realistic situations. IEEE International Conference on Computer Vision and Pattern Recognition, 2014. (400+ citations by Google Scholar) (CVPR) （国际顶级会议）
[26] J. Chen, D. Yi, J. Yang, G. Zhao, S. Li, and M. Pietikäinen, Learning Mappings for Face Synthesis from Near Infrared to Visual Light Images, IEEE International Conference on Computer Vision and Pattern Recognition, 2009 (116 citations by Google Scholar, Google 统计计算机视觉&模式识别领域影响力最高的刊物) (CVPR) （国际顶级期刊）
[27] J. Chen, S. Shan, G. Zhao, X. Chen, W. Gao, and M. Pietikäinen. A Robust Descriptor based on Weber's Law. IEEE International Conference on Computer Vision and Pattern Recognition, CVPR 2008 (74 citations by Google Scholar) (CVPR) （国际顶级会议）
[28] S. Yan, S. Shan, X. Chen, W. Gao, and J. Chen. Matrix-Structural Learning (MSL) of Cascaded Classifier from Enormous Training Set. IEEE International Conference on Computer Vision and Pattern Recognition, 2007 (40 citations by Google Scholar) (CVPR) （国际顶级会议）
[29] J. Chen, V. Kellokumpu, G. Zhao, M. Pietikäinen, RLBP: robust local binary pattern, British machine vision conference, 2013 (90 citations by Google Scholar) (BMVC) （国际顶级会议）
[30] Zhongyi Huang, Yao Ding, Guoli Song, Lin Wang, Ruizhe Geng, Hongliang He, Shan Du, Xia Liu, Yonghong Tian, Yongsheng Liang, S. Kevin Zhou, and Jie Chen; BCData: A Large-Scale Dataset and Benchmark for Cell Detection and Counting，Medical Image Computing and Computer Assisted Intervention Society （MICCAI） 2020, （国际顶级会议）[1]