基本信息

 

 

 

史金钢,博士,

软件学院副教授,博士生导师

入选西安交通大学青年拔尖人才计划

联系方式

本人隶属龚怡宏教授课题组,常年招收博士、硕士研究生(可招收计算机科学与技术【081200】专业的硕士、博士研究生以及软件工程【085212】专业的硕士研究生)。欢迎对计算机视觉、机器学习等研究领域感兴趣的优秀学生推免或报考!

欢迎对计算机视觉领域感兴趣的本科生联系课题组进行实习和研究!

有意者请邮件联系:

jingang[AT] mail.xjtu.edu.cn

jingang.shi[AT]hotmail.com

 

 

站点计数器

研究领域

工作经历:

2020至今 :                           西安交通大学软件学院副教授、博士生导师

2017-2020                     Center for Machine Vision and Signal Analysis, University of Oulu Finland                           

                                                        博士后研究员 Advised by Prof. Guoying Zhao(IEEE/IAPR Fellow) 

From Sep. 2019 to Dec. 2019   Multimedia and Human Understanding Group          University of Trento, Italy                                      Advised by Prof. Nicu Sebe(IAPR Fellow) 

2015-2017                     中国电子科技集团公司电子科学研究院 国家工程实验室

​​​​​教育经历:

2009-2015       西安交通大学信息与通信工程专业,获博士学位

2008-2009       西安交通大学信息与通信工程专业硕博连读

2003-2007       西安交通大学少年班,信息工程专业学习获学士学位

  • 目前研究工作集中在计算机视觉,机器学习,深度学习领域,主要研究方向包括:图像的超分辨率重建情绪检测与表情分析,行为识别,人脸活体检测,基于人脸视频的远程微弱生理信号检测及健康分析,多模态学习等内容。迄今在IEEE TIPIEEE TMMIEEE TCSVTPattern Recognition等国际著名期刊和会议上发表文章30余篇,曾受邀担任ICME 2021等多个国际会议的Area ChairTechnical Committee Member并担任TPAMI,IJCV等多个国际著名期刊审稿人。现主持国家自然科学基金项目“真实非受控场景下的人脸图像超分辨率重建技术研究”,曾作为项目负责人主持芬兰技术促进协会课题“Low-resolution face analysis in the wild”。作为项目共同主持人参与芬兰科学院ICT 2023项目“Context-aware autonomous neural network learning”,作为算法负责人参与芬兰科学院重点项目“Cardiac beat to beat variability analysis from remote videos for health service”,作为项目经理参与Business Finland项目“Quantifying Human Experience for Increased Intelligence Within Work Teams and in the Customer Interface”。
  • 部分代表性论文: 谷歌学术:https://scholar.google.com/citations?hl=en&user=N2ftCz4AAAAJ&view_op=list_works&sortby=pubdate

  • Zitong Yu, Yuming Shen, Jingang Shi, Hengshuang Zhao, Yawen Cui, Jiehua Zhang, Philip H. S. Torr, Guoying Zhao: PhysFormer++: Facial Video-based Physiological Measurement with SlowFast Temporal Difference Transformer. International Journal on Computer Vision, 2023

  • Jianwei Li, Zitong Yu, Jingang Shi: Learning Motion-Robust Remote Photoplethysmography through Arbitrary Resolution Videos. AAAI 2023

  • S Dong, Y Gong, J Shi, M Shang, X Tao, X Wei, X Hong, T Zhou Brain Cognition-Inspired Dual-Pathway CNN Architecture for Image Classification, IEEE Transactions on Neural Networks and Learning Systems,2023

  • Yantao Ji, Peilin Jiang, Jingang Shi, Yu Guo, Ruiteng Zhang, Fei Wang: Information-Growth Swin Transformer Network for Image Super-Resolution. ICIP 2022: 3993-3997

  • 31  Jingang Shi, Yusi Wang, Songlin Dong, Xiaopeng Hong, Zitong Yu, Fei Wang, Yihong Gong, IDPT: Interconnected Dual Pyramid Transformer for Face Super-Resolution, IJCAI 2022

  • 30. Zitong Yu, Yuming Shen, Jingang Shi, Hengshuang Zhao, Philip Torr, Guoying Zhao, PhysFormer: Facial Video-based Physiological Measurement with Temporal Difference Transformer, CVPR 2022

    29. Yu Liu, Xiaopeng Hong, Xiaoyu Tao, Songlin Dong, Jingang Shi, Yihong Gong, Model Behavior Preserving for Class-Incremental Learning, IEEE Transactions on Neural Networks and Learning Systems, 2022

    28. Yu Liu, Xiaopeng Hong, Xiaoyu Tao, Songlin Dong, Jingang Shi, Yihong Gong, Structural Knowledge Organization and Transfer for Class-Incremental Learning, ACM Multimedia Asia, 1-7

    27. W Peng, J Shi, T Varanka, G Zhao Rethinking the ST-GCNs for 3D skeleton-based human action recognition, Neurocomputing 454, 45-53,2021

    26. Z Yu, X Li, J Shi, Z Xia, G Zhao, Revisiting pixel-wise supervision for face anti-spoofing, IEEE Transactions on Biometrics, Behavior, and Identity Science, 2021

    25. W Peng, J Shi, G Zhao,Spatial temporal graph deconvolutional network for skeleton-based human action recognition IEEE Signal Processing Letters 28, 244-248

    24 W. Peng, J. Shi, Z. Xia and G. Zhao. " Mix dimension in poincaré geometry for 3d skeleton-based action recognition", Proc. the 28th ACM International Conference on Multimedia, 2020, pp. 1432-1440.

    23  Z. Yu, X. Li, X. Niu, J. Shi and G. Zhao. " Face anti-spoofing with human material perception", Proc. European Conference on Computer Vision, 2020, pp. 557-575.

    22 J. Shi, I. Alikhani, X. Li, Z. Yu, T. Seppanen and G. Zhao. "Atrial Fibrillation Detection from Face Video by Fusing Subtle Variations", IEEE Transactions on Circuits and Systems for Video Technology, vol.30, no.8, pp. 2781 - 2795, 2020. (Impact Factor: 4.046)

    21  W. Peng, J. Shi, and G. Zhao. "Spatial Temporal Graph Deconvolutional Network for Skeleton-based Human Action Recognition" IEEE Signal Processing Letters, vol. 28, pp. 244-248, 2021.(Impact Factor: 3.105)

    20 H. Chen, X. Liu, J. Shi and G. Zhao. “Temporal Hierarchical Dictionary Guided Decoding for Online Gesture Segmentation and Recognition”, IEEE Transactions on Image Processing, vol.29, pp. 9689 - 9702, 2020. (Impact Factor: 6.79)

    19  Z. Yu, X. Li, X. Niu, J. Shi and G. Zhao. “AutoHR: A strong end-to-end baseline for remote heart rate measurement with neural searching”, IEEE Signal Processing Letters, vol. 27, pp. 1245-1249, 2020.(Impact Factor: 3.105)

    18 J. Shi and G. Zhao. "Face Hallucination via Coarse-to-fine Recursive Kernel Regression Structure", IEEE Transactions on Multimedia,  vol.21, no.9, pp.2223-2236, 2019. (Impact Factor: 5.452)

    17  J. Shi, X. Liu, Y. Zong, C. Qi and G. Zhao, "Hallucinating Face Image by Regularization Models in High-Resolution Feature Space", IEEE Transactions on Image Processing, vol.27, no.6, pp. 2980-2995, 2018. (Impact Factor: 6.79)

    16 Y. Zong, W. Zheng, X. Huang, J. Shi, Z. Cui, G. Zhao. Domain regeneration for cross-database micro-expression recognitionIEEE Transactions on Image Processing, vol.27, no.5, pp. 2484-2498, 2018.(Impact Factor: 6.79)

    15 J. Shi, X. Liu, C. Qi. "Global consistency, local sparsity and pixel correlation: A unified framework for face hallucination", Pattern Recognition, vol. 47, no. 11, pp. 3520–3534, 2014. (Impact Factor: 5.898)

    14 J. Shi, C. Qi. "From Local Geometry to Global Structure: Learning Latent Subspace for Low-resolution Face Image Recognition", IEEE signal processing letters, vol. 22, no. 5, pp. 554–558, 2015.

         (Impact Factor: 3.105)

    13 J. Shi, C. Qi. "Kernel-Based Face Hallucination via Dual Regularization PriorsIEEE signal processing letters, vol. 22, no. 8, pp. 1189–1193, 2015. (Impact Factor: 3.105)

    12 M. Tang, Y. Zong, W. Zheng, J. Dai, J. Shi, P. Song "Micro-Expression Recognition by Leveraging Color Space InformationIEICE Transactions on Information and Systems, vol. 102, no. 6, pp. 1222–1226, 2019.

    11 L. Li, X. Zhou, Y. Zong, W. Zheng, X. Chen, J. Shi, P. Song "Unsupervised Cross-Database Micro-Expression Recognition Using Target-Adapted Least-Squares RegressionIEICE Transactions on Information and Systems, vol. 102, no. 7, pp. 1417–1421, 2019.

    10 J. Shi, C. Qi. "An Image Inpainting Algorithm Based on Sparse Modeling with Double Constraints"Journal of Xi’an Jiaotong University, vol. 46, no. 2, pp. 6–10, 2012.

    9 W. Peng, J. Shi, Z. Xia and G. Zhao. " Mix dimension in poincaré geometry for 3d skeleton-based action recognition", Proc. the 28th ACM International Conference on Multimedia, 2020, pp. 1432-1440.

    8  Z. Yu, X. Li, X. Niu, J. Shi and G. Zhao. " Face anti-spoofing with human material perception", Proc. European Conference on Computer Vision, 2020, pp. 557-575.

    7 J. Shi, C. Qi. "Face hallucination based on PCA dictionary pairs", Proc. the 20th IEEE International Conference on Image Processing, Melbourne, Australia, 2013, pp.933-937.

    6 J. Shi, C. Qi. "Sparse modeling based image inpainting with local similarity constraint", Proc. the 20th IEEE International Conference on Image Processing, Melbourne, Australia, 2013, pp.1371-1375.

    5 J. Shi, C. Qi, “A nonlocal exemplar-based inpainting algorithm,” Proc. the 20th National Conference on Multimedia Technology, Beijing, China, 2011. (In Chinese)

    4 G. Li , J. Shi, J. Peng, G. Zhao, “Micro-expression Recognition Under Low-resolution Cases”, Proc. the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, 2019.

    3 X. Li, I. Alikhani, J. Shi, T. Seppänen, J. Junttila, K. Majamaa-Voltti, M. Tulppo and G. Zhao, “The OBF Database: A Large Face Video Database for Remote Physiological Signal Measurement and Atrial Fibrillation DetectionProc. the 13th IEEE International Conference on Automatic Face and Gesture Recognition, 2018.

    2 M. Qiao, T. Wang, Y. Dong, J. Shi, J. Teng and H. Snoussi, "Real time object tracking based on local texture feature with correlation filter", Proc. the 21st IEEE International Conference on Digital Signal Processing, Beijing, China, 2016.

    1 Z. Zha, X. Liu, Z. Zhou, X. Huang, J. Shi, and X. Zhang, "Image denoising via group sparsity residual constraint", Proc. the 42nd IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), NEW ORLEANS, USA, 2017.

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