Context Encoders: Feature Learning by Inpainting 閱讀筆記
Github 目錄 1. 介紹 2. 架構 3. 數據生成 1. 介紹 無監督學習， 圖像修復 學習深層特徵 通過下圖可以看到效果很好 2. 架構 link 採用類似encoder-decoder架構, L2 loss使圖片重建相近，adversarial loss使圖片清晰 encoder和decoder之間使用channel-wise FC層相連(因爲修復需要四周的context,而單純con
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相關文章
- 1. Context Encoders: Feature Learning by Inpainting
- 2. 論文閱讀筆記之——《Learning Pyramid-Context Encoder Network for High-Quality Image Inpainting》
- 3. 論文：Variational Graph Auto-Encoders閱讀筆記
- 4. 【論文閱讀筆記】Multi-scale context aggregation by dilated convolutions
- 5. 《Knowledge Base Completion By Learning...》閱讀筆記
- 6. Learning to Generate Questions by Learning What not to Generate閱讀筆記
- 7. Machine Learning & Deep Learning 論文閱讀筆記
- 8. 閱讀筆記 CCL: Cross-modal Correlation Learning with Multi-grained Fusion by Hierarchical Network
- 9. BiSeNet閱讀筆記
- 10. 《Improving Event Coreference Resolution by Learning Argument Compatibility from Unlabeled Data》閱讀筆記