論文閱讀筆記：Perceptual Losses for Real-Time Style Transfer and Super-Resolution
這篇文章是ECCV2016的一篇文章，主要是提出了一種全新的Loss用於圖像風格轉換和圖像超分辨。 整體框架如上圖所示，分爲兩個網絡，圖像轉換網絡和損失網絡，其中圖像轉換網絡是深度殘差網絡，將圖片轉換爲^ y = fW (x) 。我們訓練圖像轉換網絡來最小化損失網絡的輸出值加權和。損失網絡部分部分是16層的VGG網絡，它的特定層拿出來作爲損失函數。 我們將這個損失函數與這兩個函數作對比實驗。在圖像
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相關文章
- 1. 論文解讀之Perceptual Losses for Real-Time Style Transfer and Super-Resolution
- 2. Perceptual Losses for Real-Time Style Transfer and Super-Resolution
- 3. Perceptual Losses for Real-Time Style Transfer and Super-Resolution閱讀（一）
- 4. Perceptual Losses for Real-Time Style Transfer and Super-Resolution閱讀（二）
- 5. Perceptual Losses for Real-Time Style Transfer and Super-Resolution and Super-Resolution 論文筆記
- 6. Perceptual Losses對SR論文閱讀筆記
- 7. 論文《Perceptual Losses for Real-Time Style Transfer and Super-Resolution》
- 8. [Style Transfer]——Perceptual Losses for Real-Time Style Transfer and Super-Resolution
- 9. [論文筆記] Perceptual Losses for Real-Time Style Transfer and Super-Resolution
- 10. 項目實訓（二十四）Perceptual Losses for Real-Time Style Transfer and Super-Resolution閱讀