67 citations · 129 across the 5 of their papers we have counts for
5 papers
Image-specific Convolutional Kernel Modulation for Single Image Super-resolution
Yuanfei Huang, Jie Li, Yanting Hu +2
Recently, deep-learning-based super-resolution methods have achieved excellent performances, but mainly focus on training a single generalized deep network by feeding numerous samp…
Transitional Learning: Exploring the Transition States of Degradation for Blind Super-resolution
Yuanfei Huang, Jie Li, Yanting Hu +2
Being extremely dependent on iterative estimation of the degradation prior or optimization of the model from scratch, the existing blind super-resolution (SR) methods are generally…
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…
Channel-wise and Spatial Feature Modulation Network for Single Image Super-Resolution
Yanting Hu, Jie Li, Yuanfei Huang +1
The performance of single image super-resolution has achieved significant improvement by utilizing deep convolutional neural networks (CNNs). The features in deep CNN contain diffe…
Single Image Super-Resolution via Cascaded Multi-Scale Cross Network
Yanting Hu, Xinbo Gao, Jie Li +2
The deep convolutional neural networks have achieved significant improvements in accuracy and speed for single image super-resolution. However, as the depth of network grows, the i…