9 citations · 12 across the 4 of their papers we have counts for
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Interpretable Detail-Fidelity Attention Network for Single Image Super-Resolution
Yuanfei Huang, Jie Li, Xinbo Gao +2
Benefiting from the strong capabilities of deep CNNs for feature representation and nonlinear mapping, deep-learning-based methods have achieved excellent performance in single ima…
AIM 2019 Challenge on Real-World Image Super-Resolution: Methods and Results
Andreas Lugmayr, Martin Danelljan, Radu Timofte +18
This paper reviews the AIM 2019 challenge on real world super-resolution. It focuses on the participating methods and final results. The challenge addresses the real world setting,…
Distilling with Residual Network for Single Image Super Resolution
Xiaopeng Sun, Wen Lu, Rui Wang +1
Recently, the deep convolutional neural network (CNN) has made remarkable progress in single image super resolution(SISR). However, blindly using the residual structure and dense s…
A Gated Peripheral-Foveal Convolutional Neural Network for Unified Image Aesthetic Prediction
Xiaodan Zhang, Xinbo Gao, Wen Lu +1
Learning fine-grained details is a key issue in image aesthetic assessment. Most of the previous methods extract the fine-grained details via random cropping strategy, which may un…