activity
20182022
most citedInterpretable Detail-Fidelity Attention Network for Single Image Super-Resolution

67 citations · 129 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2022

NTIRE 2022 Challenge on Efficient Super-Resolution: Methods and Results

Yawei Li, Kai Zhang, Radu Timofte +108

This paper reviews the NTIRE 2022 challenge on efficient single image super-resolution with focus on the proposed solutions and results. The task of the challenge was to super-reso…

eess.IV2021

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…

cs.CV2021

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…

cs.CV2020★ 67 cited

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…

cs.CV2019

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,…

cs.CV2018★ 20 cited

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…

cs.CV2018★ 42 cited

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…