Occlusion-free Face Alignment: Deep Regression Networks Coupled with De-corrupt AutoEncoders
這篇論文是我總結的，感覺思路還是不錯的，目前主流的處理圖像方式，或者人臉對齊方式都是使用了深度學習，因爲深度學習對於人臉對齊具有很好的效果，並且對於遮擋也會有一定的容忍性。 這篇論文是：Occlusion-free Face Alignment: Deep Regression Networks Coupled with De-corrupt AutoEncoders。
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- 1. 論文筆記：Occlusion-free Face Alignment: Deep Regression Networks Coupled with De-corrupt Auto-Encoders
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相關文章
- 1. 論文筆記：Occlusion-free Face Alignment: Deep Regression Networks Coupled with De-corrupt Auto-Encoders
- 2. Deep Cascaded Regression for Face Alignment（DCR2015）
- 3. Direct Shape Regression Networks for End-to-End Face Alignment
- 4. (Face Alignment) One Millisecond Face Alignment with an Ensemble of Regression Trees 筆記
- 5. End-to-end 3D face reconstruction with deep neural networks
- 6. Deep Clustering with Convolutional Autoencoders
- 7. DeepID3: Face Recognition with Very Deep Neural Networks
- 8. Learning to Track at 100 FPS with Deep Regression Networks
- 9. 人臉對齊--Face Alignment by Explicit Shape Regression
- 10. POCR-project-out cascaded regression for face alignment