Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks閱讀筆記
Abstract： 挑戰：（1）人臉不同的姿態（2）光照（3）遮擋。 本文研究：提出了一種深度級聯的多任務框架，利用框架之間的內在相關性來提高它們的性能。 框架：級聯結構——三層深度卷積網絡，以粗到細的方式預測人臉和地標位置。 策略：在線困難樣本挖掘策略——自動提高算法的性能而不需要人工樣本篩選。 優勢：在人臉檢測方面：以FDDB和WIDER FACE爲基準。 在人臉對齊方面：以AFLW爲基
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- 4. 論文筆記：Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
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相關文章
- 1. 論文筆記1.3——Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
- 2. 論文筆記1.2——Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
- 3. 論文筆記1——Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
- 4. 論文筆記：Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
- 5. 論文：Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks 閱讀筆記
- 6. MTCNN解讀：Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
- 7. 論文解讀——Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks（二）
- 8. 論文解讀——Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks（一）
- 9. 論文Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
- 10. Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks論文理解