72 citations · 85 across the 3 of their papers we have counts for
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cs.CV2023★ 2 cited
Crafting Training Degradation Distribution for the Accuracy-Generalization Trade-off in Real-World Super-Resolution
Ruofan Zhang, Jinjin Gu, Haoyu Chen +3
Super-resolution (SR) techniques designed for real-world applications commonly encounter two primary challenges: generalization performance and restoration accuracy. We demonstrate…
cs.CV2016★ 72 cited
Deep Convolution Networks for Compression Artifacts Reduction
Ke Yu, Chao Dong, Chen Change Loy +1
Lossy compression introduces complex compression artifacts, particularly blocking artifacts, ringing effects and blurring. Existing algorithms either focus on removing blocking art…
cs.CV2016★ 11 cited
Accelerating the Super-Resolution Convolutional Neural Network
Chao Dong, Chen Change Loy, Xiaoou Tang
As a successful deep model applied in image super-resolution (SR), the Super-Resolution Convolutional Neural Network (SRCNN) has demonstrated superior performance to the previous h…