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赵凯 (Kai ZHAO)

Hi😊 我是赵凯,现在是南开大学计算机💻专业博士生,导师是程明明教授。 我在上海大学完成本科和硕士学业,我的硕士导师是沈为博士。 我的研究兴趣主要是 计算机视觉👁️, 统计学习🧠和 强化学习🤖。 通俗上我的研究领域属于 人工智能 的范畴 (虽然我不愿意这么叫),我对统计学习模型和背后的数学原理和理论解释很感兴趣(虽然我没有数学专业背景)。 您可以访问http://kaizhao.net/research来详细了解我的研究和我公开发表的论文。 这里是我的简历:http://kaizhao.net/cv

我对历史,特别是古代经济和科技史比较感兴趣。 黄仁宇 (Ray Huang)魏斐德 (Frederic Wakeman)是我最喜欢的两位历史学家。

我是MOBA游戏DOTA2的云玩家,花在看比赛的时间甚于自己打游戏的时间。 从 DOTA1 时代过来陆陆续续打了七八年,但这并不影响我是个菜鸡。 这里是我的DOTA2游戏数据:https://www.dotabuff.com/players/416446484

偶尔会写一些技术博客文章放在http://kaizhao.net/posts。 这里有有一些平常出去玩儿拍的照片:http://kaizhao.net/gallery

联系方式:

社交媒体:

照片

偶尔出去玩拍拍照片,也拍拍家里的花草 🌼 动物 🐕 (更多的照片可以点 这里)

公开发表的论文:

  1. Qi Han*, Kai Zhao*, Jun Xu, Mingg-Ming Cheng. Deep Hough Transform for Semantic Line Detection. (* denotes equal contribution) [arXiv: 2003.04676]
  2. Xin-Yu Zhang*, Kai Zhao*, Taihong Xiao, Ming-Ming Cheng, Ming-Hsuan Yang. Model-Agnostic Structured Sparsification with Learnable Channel Shuffle. (* denotes equal contribution) [arXiv: 2002.08127]
  3. Kai Zhao, Shanghua Gao, Wenguan Wang, Ming-Ming Cheng. Optimizing the F-measure for Threshold-free Salient Object Detection. International conference on computer vision (ICCV), Seoul, Korea, 2019. [Project page] [PDF] []
    @InProceedings{zhao2019optimizing,
      author    = {Kai Zhao and Shanghua Gao and Wenguan Wang and Ming-ming Cheng},
      title     = {Optimizing the {F}-measure for Threshold-free Salient Object Detection},
      booktitle = {The IEEE International Conference on Computer Vision (ICCV)},
      pages     = {8849-8857},
      month     = {Oct},
      year      = {2019},
      url       = {http://kaizhao.net/fmeasure}
    }
    
  4. Kai Zhao, Jingyi Xu, Ming-Ming Cheng. RegularFace: Deep Face Recognition via Exclusive Regularization. IEEE conference on Computer Vision and Patterm Recognition (CVPR), Long Beach, USA, 2019. [PDF] [project page] []
    @InProceedings{zhao2019regularface,
      author    = {Zhao, Kai and Xu, Jingyi and Cheng, Ming-Ming},
      title     = {RegularFace: Deep Face Recognition via Exclusive Regularization},
      booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
      pages     = {1136-1144},
      month     = {June},
      year      = {2019}
    }
    
  5. Kai Zhao, Wei Shen, Shanghua Gao, Dandan Li, Ming-Ming Cheng. Hi-Fi: Hierarchical Feature Integration for Skeleton Detection. International Joint Conference on Artificial Intelligence (IJCAI), Stockholm, Sweden, 2018. [PDF] [LaTeX Source] [Project page] []
    @inproceedings{zhao2018hifi,
      title     = {Hi-{F}i: Hierarchical Feature Integration for Skeleton Detection},
      author    = {Kai Zhao and Wei Shen and Shanghua Gao and Dandan Li and Ming-Ming Cheng},
      booktitle = {Proceedings of the Twenty-Seventh International Joint Conference on
                  Artificial Intelligence, {IJCAI-18}},
      publisher = {International Joint Conferences on Artificial Intelligence Organization},
      pages     = {1191--1197},
      year      = {2018},
      month     = {7},
      doi       = {10.24963/ijcai.2018/166},
      url       = {http://kaizhao.net/hifi},
    }
    
  6. Wei Shen, Kai Zhao, Yilu Guo, Alan Yuille. Label Distribution Learning Forests. Proceedings of advances in neural information processing systems(NIPS), Long Beach, USA, 2017. [arXiv:1702.06086] [Project Page] [Code] []
    @InProceedings{shen2017label,
      title     = {Label Distribution Learning Forests},
      author    = {Shen, Wei and Zhao, Kai and Guo, Yilu and Yuille, Alan},
      booktitle = {Proceedings of Advances in neural information processing systems},
      year      = {2017},
      url       = {http://kaizhao.net/ldlf},
    }
    
  7. Wei Shen, Kai Zhao, Yuan Jiang, Yan Wang, Zhijiang Zhang, Xiang Bai. Object Skeleton Extraction in Natural Images by Fusing Scale-associated Deep Side Outputs. Proceddings of the 29th IEEE Conference on Computer Vision and Pattern Recognition(CVPR), Las Vegas, USA, 2016. [arXiv:1603.09446] [Code] []
    @InProceedings{shen2016object,
      title={Object Skeleton Extraction in Natural Images by Fusing Scale-associated Deep Side Outputs},
      author={Shen, Wei and Zhao, Kai and Jiang, Yuan and Wang, Yan and Zhang, Zhijiang and Bai, Xiang},
      booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
      year={2016},
      pages={222-230},
      publisher={IEEE},
      howpublished = "\url{http://kaizhao.net/deepsk}"
    }
    
  8. Shang-Hua Gao, Ming-Ming Cheng, Kai Zhao, Xin-Yu Zhang, Ming-Hsuan Yang, Philip Torr. Res2Net: A New Multi-scale Backbone Architecture. (IEEE Trans on Pattern Analysis and Machine Intelligence, 2019) [Project Page ] [Code ]
  9. Wei Shen, Yilu Guo, Yan Wang, Kai Zhao, Bo Wang, Alan Yuille Deep Differentiable Random Forests for Age Estimation.. (IEEE Trans on Pattern Analysis and Machine Intelligence, 2019)
  10. Wei Shen, Kai Zhao, Yuan Jiang, Yan Wang, Xiang Bai, Alan Yuille. DeepSkeleton: Learning Multi-task Scale-associated Deep Side Outputs for Object Skeleton Extraction in Natural Images. (IEEE Trans on Image Processing, 2017) [arXiv:1609.03659] [Project Page ] [Code] [SK-LARGE dataset] []
    @article{shen2017deepskeleton,
      title={DeepSkeleton: Learning Multi-task Scale-associated Deep Side Outputs for Object Skeleton Extraction in Natural Images},
      author={Shen, Wei and Zhao, Kai and Jiang, Yuan and Wang, Yan and Bai, Xiang and Yuille, Alan},
      journal={IEEE Transactions on Image Processing},
      volume={26},
      number={11},
      pages={5298-5311},
      year={2017},
      publisher={IEEE},
      howpublished = "\url{http://kaizhao.net/deepsk}"
    }
    
  11. Object Skeleton Detection with Fully Convolutional Neural Networks. Master's thesis, in Chinese(中文硕士学位论文). [PDF] [LaTeX Source] [LaTeX Template]

CVPR, ICCV 和 ECCV 是计算机视觉领域三大国际顶级会议;CVPR,ICCV,IJCAI 是中国计算机学会(CCF)工智能领域的 A 类会议。

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