Searching Central Differene Convolutional Networks for Face Anti-Spoofing隨筆
一.簡介 論文裏說相對與普通的卷積方法，CDC(Central Difference Convolution)中心差分卷積更能夠提取攻擊模式下固有的特徵，例如晶格僞影在不同的環境變化下，文章的主要工作有： （1）設計了一種新的卷積算子叫中心差分卷積（CDC） 對於FAS任務，由於其對不同環境下不變的細粒度特徵具有顯著的表示能力。在不引入任何額外參數的情況下，CDC可以代替普通的卷積，直接將原來的卷
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相關文章
- 1. Fast Face-swap Using Convolutional Neural Networks
- 2. Convolutional Neural Networks for Visual Recognition
- 3. 【DDFD】《Multi-view Face Detection Using Deep Convolutional Neural Networks》
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- 5. Searching for MobileNetV3筆記
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- 7. 《Character-level Convolutional Networks for Text Classification》
- 8. FCN—— Fully Convolutional Networks for Semantic Segmentation
- 9. Joint Head Pose Estimation with Multi-task Cascaded Convolutional Networks for Face Alignment
- 10. 2019 FeatherNets: Convolutional Neural Networks as Light as Feather for Face Anti-spoofing