FERAtt: Facial Expression Recognition with Attention Net閱讀筆記
預覽 這是一篇CVPRW2019的論文，作者將Attention機制引入到人臉表情識別中。提出Attention model，並寫出了一個合成圖片的生成器，模型對噪聲有較強的魯棒性，並在CK+，BU-3DFE數據集上有一定的性能提升。 原文地址和github源碼地址 原文地址 github源碼地址 Problem Recent developments for the facial express
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相關文章
- 1. Facial Expression Recognition by De-expression Residue Learning閱讀筆記
- 2. 2018CVPR：Joint Pose and Expression Modeling for Facial Expression Recognition閱讀筆記
- 3. Suppressing Uncertainties for Large-Scale Facial Expression Recognition閱讀筆記
- 4. CVPR2020: Suppressing Uncertainties for Large-Scale Facial Expression Recognition 閱讀隨筆
- 5. A Compact Deep Learning Model for Robust Facial Expression Recognition 閱讀筆記
- 6. Deep Facial Expression Recognition: A Survey 筆記
- 7. Facial Expression Recognition Using KCCA
- 8. Region Attention Networks for Pose and Occlusion Robust Facial Expression Recognition文章解讀
- 9. Deep Facial Expression Recognition: A Survey
- 10. Facial Expression Recognition by De-expression Residue Learning-論文筆記