“第二十章 人脸识别”版本间的差异

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高级读者
 
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* Insight Face [https://github.com/deepinsight/insightface]
 
* Insight Face [https://github.com/deepinsight/insightface]
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* Simple Face Recognition API [https://github.com/ageitgey/face_recognition]
 
* Face recognoition with OpenCV [https://opencv.org/][https://docs.opencv.org/3.4/da/d60/tutorial_face_main.html]
 
* Face recognoition with OpenCV [https://opencv.org/][https://docs.opencv.org/3.4/da/d60/tutorial_face_main.html]
 
* Face js: quick demo with JS [https://justadudewhohacks.github.io/face-api.js/docs/index.html]
 
* Face js: quick demo with JS [https://justadudewhohacks.github.io/face-api.js/docs/index.html]
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==高级读者==
 
==高级读者==
  
* Brunelli R, Poggio T. Face recognition: Features versus templates[J]. IEEE transactions on pattern analysis and machine intelligence, 1993, 15(10): 1042-1052. [https://www.academia.edu/download/7233387/com-pami1993-10-01.pdf]
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* Brunelli R, Poggio T. Face recognition: Features versus templates[J]. IEEE transactions on pattern analysis and machine intelligence, 1993, 15(10): 1042-1052. [https://www.researchgate.net/profile/Tomaso-Poggio-2/publication/3192217_Face_Recognition_Features_Versus_Templates/links/09e4150e6e9231f489000000/Face-Recognition-Features-Versus-Templates.pdf]
 
* Sun Y, Wang X, Tang X. Deep learning face representation from predicting 10,000 classes[C]//Proceedings of the IEEE conference on computer vision and pattern recognition. 2014: 1891-1898. [https://openaccess.thecvf.com/content_cvpr_2014/papers/Sun_Deep_Learning_Face_2014_CVPR_paper.pdf]
 
* Sun Y, Wang X, Tang X. Deep learning face representation from predicting 10,000 classes[C]//Proceedings of the IEEE conference on computer vision and pattern recognition. 2014: 1891-1898. [https://openaccess.thecvf.com/content_cvpr_2014/papers/Sun_Deep_Learning_Face_2014_CVPR_paper.pdf]
 
* Y. Taigman, M. Yang, M. Ranzato, and L. Wolf. DeepFace: Closing the gap to human-level performance in face verification. In Proc. CVPR, 2014.[https://openaccess.thecvf.com/content_cvpr_2014/papers/Taigman_DeepFace_Closing_the_2014_CVPR_paper.pdf]
 
* Y. Taigman, M. Yang, M. Ranzato, and L. Wolf. DeepFace: Closing the gap to human-level performance in face verification. In Proc. CVPR, 2014.[https://openaccess.thecvf.com/content_cvpr_2014/papers/Taigman_DeepFace_Closing_the_2014_CVPR_paper.pdf]
 
* 王东,利节,许莎, 人工智能,第一章,认识你的脸,2019 [http://aibook.cslt.org]
 
* 王东,利节,许莎, 人工智能,第一章,认识你的脸,2019 [http://aibook.cslt.org]

2023年8月13日 (日) 01:45的最后版本


教学资料

扩展阅读

  • 百度百科:脸盲症 [3]
  • 听说你也有脸盲症?这可是病,治不好的那种! [4]
  • AMiner 报告:人脸识别报告[5]


视频展示

  • 为什么脸盲症会认不清人脸? [6]
  • ArcFace 视频展示 [7]

演示链接

  • BetaFace: detect face and key points [8]
  • Face detection[9]
  • Face analyzer [10]

开发者资源

  • Insight Face [11]
  • Simple Face Recognition API [12]
  • Face recognoition with OpenCV [13][14]
  • Face js: quick demo with JS [15]


高级读者

  • Brunelli R, Poggio T. Face recognition: Features versus templates[J]. IEEE transactions on pattern analysis and machine intelligence, 1993, 15(10): 1042-1052. [16]
  • Sun Y, Wang X, Tang X. Deep learning face representation from predicting 10,000 classes[C]//Proceedings of the IEEE conference on computer vision and pattern recognition. 2014: 1891-1898. [17]
  • Y. Taigman, M. Yang, M. Ranzato, and L. Wolf. DeepFace: Closing the gap to human-level performance in face verification. In Proc. CVPR, 2014.[18]
  • 王东,利节,许莎, 人工智能,第一章,认识你的脸,2019 [19]