DCGAN應用: Semantic Image Inpainting with Deep Generative Models
本篇blog內容基於殘缺圖像補全Semantic Image Inpainting with Deep Generative Models（CVPR2017），使用數據庫celabA，包含了202599張頭像圖片。node 1、數據集 每行包括5張圖片：第一列是數據庫原始圖片；第二列是隨機取出80%的像素點圖片；第三列是使用補全方法對第二列的修復結果；第四列是原始數據中間被扣掉一大塊的圖片；第五列
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相關文章
- 1. DCGAN應用: Semantic Image Inpainting with Deep Generative Models
- 2. 圖像修復論文「Generative Image Inpainting with Contextual Attention」
- 3. CS224W 10.1-Deep Generative Models for Graphs
- 4. 《Generative Image Inpainting with Adversarial Edge Learning》論文閱讀之edge-connect
- 5. Free-Form Image Inpainting with Gated Convolution
- 6. Review of Semantic Segmentation with Deep Learning
- 7. Image Inpainting via Generative Multi-column Convolutional Neural Networks
- 8. Semantic Segmentation---DeepLab V1:Semantic Image Segmentation with Deep Convolutional Nets..（論文解讀二）
- 9. Semantic Segmentation -- (DeepLabv1)Semantic image segmentation with deep convolutional ... CRFs論文解讀
- 10. Deep Semantic Hashing with Generative Adversarial Networks 論文review（翻譯）