20 citations · 45 across the 5 of their papers we have counts for
5 papers
FAN: Frequency Aggregation Network for Real Image Super-resolution
Yingxue Pang, Xin Li, Xin Jin +4
Single image super-resolution (SISR) aims to recover the high-resolution (HR) image from its low-resolution (LR) input image. With the development of deep learning, SISR has achiev…
AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results
Pengxu Wei, Hannan Lu, Radu Timofte +68
This paper introduces the real image Super-Resolution (SR) challenge that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ECCV 2020. This ch…
LIRA: Lifelong Image Restoration from Unknown Blended Distortions
Jianzhao Liu, Jianxin Lin, Xin Li +3
Most existing image restoration networks are designed in a disposable way and catastrophically forget previously learned distortions when trained on a new distortion removal task.…
Learning Disentangled Feature Representation for Hybrid-distorted Image Restoration
Xin Li, Xin Jin, Jianxin Lin +5
Hybrid-distorted image restoration (HD-IR) is dedicated to restore real distorted image that is degraded by multiple distortions. Existing HD-IR approaches usually ignore the inher…
VESR-Net: The Winning Solution to Youku Video Enhancement and Super-Resolution Challenge
Jiale Chen, Xu Tan, Chaowei Shan +2
This paper introduces VESR-Net, a method for video enhancement and super-resolution (VESR). We design a separate non-local module to explore the relations among video frames and fu…