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夏桂松,男,1983年生,武汉大学教授,博士生导师。2005年和2007年先后在武汉大学获得学士和硕士学位,2011年3月获得 法国巴黎高科电信学院 (Telecom ParisTech) 博士学位。 2011年4月至2012年12月先后在 法国巴黎高科电信学院LTCI实验室 法国国家科学研究中心 (CNRS) -决策数学研究所 (CEREMADE) 从事博士后研究工作。 长期从事图像分析和理解以及模式识别等领域的研究工作,在包括 International Journal of Computer Vision (IJCV), IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), IEEE Trans. on Image Processing (TIP) , SIAM Journal on Imaging Science (SIIMS), Pattern Recognition (PR), IEEE Trans. on Geoscience and Remote Sensing (TGRS) 等国际权威期刊和CVPR、ECCV、BMVC、ICIP、ICPR等相关国际会议上发表学术论文110余篇。 现担任国际期刊 ISPRS Journal of Photogrammetry and Remote Sensing, Pattern Recognition, EURASIP Journal on Image and Video Processing Signal Processing: Image Communications Journal of Remote SensingFrontier in Computer Science: Computer Vision 等期刊编委 (Associate Editor),以及 IEEE Trans. on Big Data , Pattern Recognition Letter, Geo-Spatial Information Science等国际期刊客座编委 (Guest Editor)。 先后获得湖北省“楚天学子”(2013)、湖北省自然科学基金杰青(2017)、“第二届中国科协优秀科技论文”奖(2017)、湖北省自然科学奖二等奖(2018)、国家自然科学基金优青(2019)、Remote Sensing杰出贡献奖(2020)等人才项目资助和奖励。 详细个人简历

欢迎具有较好计算机/信息/数学背景的本科/硕士生攻读CAPTAIN硕/博士研究生,攻读博士研究生建议提前1年与本人邮件联系。
招生专业包括:计算机科学与技术,人工智能,摄影测量与遥感,信号与信息处理。
招生简介请参见硕/博士招聘启示

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教育经历

  • 2007.10-2011.03,法国巴黎高科电信学院 (Telecom ParisTech),图像理解,工学博士.
  • 2005.10-2007.06, 武汉大学电子信息学院,信号与信息处理,工学硕士.
  • 2001.09-2005.06,武汉大学电子信息学院,电子信息工程,工学学士.

工作经历


学术兼职


奖励荣誉

  • GRSS High Impact Paper Award, IEEE GRSS, 2022
  • 测绘科技进步一等奖,2021
  • Best Paper Candidate, IEEE CVPR, 2021
  • Outstanding Contribution Award, Remote Sensing, 2020
  • 国家自然科学基金优青获得者,2019
  • 湖北省自然科学奖二等奖,2018
  • “第二届中国科协优秀科技论文”奖,2017
  • 湖北省自然科学基金杰青获得者,2017
  • 武汉市科技局“晨光计划”,2014
  • 湖北省楚天学者(楚天学子),2013
  • 武汉大学“研究生十大学术之星”奖,2007

研究兴趣

  • 视觉信息的数学模型.
  • 图匹配问题及其应用
  • 计算机视觉与机器学习.
  • 大规模视觉场景三维重建.
  • 无人智能系统信息处理、融合与场景认知.
  • 遥感图像解译与信息挖掘.

代表学术成果

  • Learning to Extract Building Footprints from Off-Nadir Aerial Images, [PDF]. with J. Wang et. al..
    IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), in press.
  • Object Detection in Aerial Images: A Large-Scale Benchmark and Challenges, [arXiv, Dataset, Code, Model]. with J. Ding et. al.
    IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), in press.
  • Unsupervised Pretraining for Object Detection by Patch Reidentification, [arXiv]. with J. Ding et. al.
    IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), in press.
  • Unmixing Convolutional Features for Crisp Edge Detection, [arXiv, Codes]. with L. Huan et. al.
    IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), in press.
  • Learning Regional Attraction for Line Segment Detection, [PDF, Page]. with N. Xue et. al.
    IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), Vol. 43, No.6, pp.1998-2013, 2021.
  • Gliding vertex on HBB for multi-oriented object detection, [arXiv, codes]. with Y. Xu et. al.
    IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), Vol.43, No.4, pp.1452-1459, 2021.
  • A Functional Representation for Graph Matching [Project Page]. with F.-D. Wang et. al.
    IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), Vol.42, No.11, pp.2737-2754, 2020.
  • Land-Cover Classification with HR-RS Images using Transferable Deep Models [arXiv, Page]. with X.-Y. Tong et. al.
    Remote Sensing of Environment (RSE), 2020.
  • Holistically-Attracted Wireframe Parsing [arXiv]. with N. Xue et. al.
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020.
  • Learning RoI Transformer for Detecting Oriented Objects in Aerial Images [PDF], with J. Ding et. al.
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2019.
  • DOTA: A Large-scale dataset for object detection in aerial images [PDF, Project Page, gitHub]. with X. Bai et. al.
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
  • Anisotropic-scale junction detection and matching for indoor images . [PDF], with N. Xue et. al.
    IEEE Trans. on Image Processing (TIP), Vol.27, No.1, pp.78-91, 2018.
  • Texture characterization using shape co-occurrence patterns. [PDF], with G. Liu et. al.
    IEEE Trans. on Image Processing (TIP), Vol.26, No. 10, pp.5005 - 5018, 2017.
  • AID: A benchmark dataset for performance evaluation of aerial scene classification . [PDF, project-page], with J. Hu et. al.
    IEEE Trans. on Geoscience and Remote Sensing (TGRS), Vol. 55, No.7, pp.3965 - 3981, 2017.