“第二十章 人脸识别”版本间的差异
来自cslt Wiki
（→高级读者） |
|||
| （相同用户的一个中间修订版本未显示） | |||
| 第28行： | 第28行： | ||
* Insight Face [https://github.com/deepinsight/insightface] | * Insight Face [https://github.com/deepinsight/insightface] | ||
| + | * 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] | ||
| 第35行： | 第36行： | ||
==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. | + | * 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
视频展示
演示链接
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]
