2018CVPR：Joint Pose and Expression Modeling for Facial Expression Recognition阅读笔记
介绍下这篇论文 这篇论文是江苏大学张飞飞发在2018年CVPR上的一篇论文，针对姿态和表情建模来进行面部表情识别，其实就是以CGAN为基础，在上面创新。 贡献 = 创新点 这里引用他文章中的贡献： 说白了，就是提出了一个端到端的学习模型，也可以说是提出了一种网络结构，剩余两个创新点都是对第一个创新点的修饰，说这个模型能够自动生成任意姿态任意表情的人脸图像，这个模型在Multi-PIE、BU-3DF
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- 2. Facial Expression Recognition by De-expression Residue Learning阅读笔记
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- 5. A Compact Deep Learning Model for Robust Facial Expression Recognition 阅读笔记
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- 7. FERAtt: Facial Expression Recognition with Attention Net阅读笔记
- 8. CVPR2020: Suppressing Uncertainties for Large-Scale Facial Expression Recognition 阅读随笔
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相关文章
- 1. Joint Pose and Expression Modeling for Facial Expression Recognition 论文翻译
- 2. Facial Expression Recognition by De-expression Residue Learning阅读笔记
- 3. Region Attention Networks for Pose and Occlusion Robust Facial Expression Recognition文章解读
- 4. Suppressing Uncertainties for Large-Scale Facial Expression Recognition阅读笔记
- 5. A Compact Deep Learning Model for Robust Facial Expression Recognition 阅读笔记
- 6. Deep Covariance Descriptors for Facial Expression Recognition
- 7. FERAtt: Facial Expression Recognition with Attention Net阅读笔记
- 8. CVPR2020: Suppressing Uncertainties for Large-Scale Facial Expression Recognition 阅读随笔
- 9. Deep Facial Expression Recognition: A Survey 笔记
- 10. Facial Expression Recognition Using KCCA