Recovering Realistic Texture in Image Super-resolution by Deep Spatial Feature Transform
Abstract 恢復自然和逼真的紋理仍然是一個具有挑戰性的問題,可以忠實與語義類恢復圖片紋理。 我們僅需在基於語義分割概率圖的單個網絡中調製幾個中間層的特徵。這可以通過新穎的空間特徵變換（SFT）層來實現，該層生成用於空間特徵調製的仿射變換參數。 SFT層可以與具有相同損耗功能的SR網絡一起端到端地進行訓練。在測試期間，它接受任意大小的輸入圖像，並生成高分辨率圖像，只有一個前向通道以分類先驗爲條
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相關文章
- 1. Paper | Recovering Realistic Texture in Image Super-resolution by Deep Spatial Feature（講的很好，還是商湯語義加入
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- 4. Image Super-Resolution by Neural Texture Transfer
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- 9. 讀論文：Image Super-Resolution by Neural Texture Transfer
- 10. Deep Hash in Large Scale Image Retrieval