論文筆記：Occlusion-free Face Alignment: Deep Regression Networks Coupled with De-corrupt Auto-Encoders
原文地址： https://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Zhang_Occlusion-Free_Face_Alignment_CVPR_2016_paper.pdf 論文方法整體框架圖 基本方法流程 使用深度迴歸網絡（DR）預測人臉形狀 一共三層，前面兩層是非線性隱藏層，最後一層是線性迴歸層。 使用去遮擋自編
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相關文章
- 1. Occlusion-free Face Alignment: Deep Regression Networks Coupled with De-corrupt AutoEncoders
- 2. (Face Alignment) One Millisecond Face Alignment with an Ensemble of Regression Trees 筆記
- 3. Deep Cascaded Regression for Face Alignment（DCR2015）
- 4. 論文筆記1.3——Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
- 5. 《Learning Deep Representation for Face Alignment with Auxiliary Attributes》論文閱讀筆記
- 6. 論文筆記1.2——Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
- 7. 論文筆記1——Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
- 8. Learning to Track at 100 FPS with Deep Regression Networks 論文筆記
- 9. Direct Shape Regression Networks for End-to-End Face Alignment
- 10. Deep Anomaly Detection with Deviation Networks 論文筆記