Recovering Realistic Texture in Image Super-Resolution by Deep Spatial Feature Transform
Recovering Realistic Texture in Image Super-Resolution by Deep Spatial Feature Transform
Despite that convolutional neural networks (CNN) have recently demonstrated high-quality reconstruction for single-image super-resolution (SR), recovering natural and realistic texture remains a challenging problem. In this paper, we show that it is possible to recover textures faithful to semantic classes. In particular, we only need to modulate features of a …