Closed-loop Matters: Dual Regression Networks for Single Image Super-Resolution

CVPR 2020 Yong GuoJian ChenJingdong WangQi ChenJiezhang CaoZeshuai DengYanwu XuMingkui Tan

Deep neural networks have exhibited promising performance in image super-resolution (SR) by learning a nonlinear mapping function from low-resolution (LR) images to high-resolution (HR) images. However, there are two underlying limitations to existing SR methods... (read more)

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