most citedAIM 2020 Challenge on Real Image Super-Resolution: Methods and Results

20 citations · 25 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV20212 cited

Learning Omni-frequency Region-adaptive Representations for Real Image Super-Resolution

Xin Li, Xin Jin, Tao Yu +4

Traditional single image super-resolution (SISR) methods that focus on solving single and uniform degradation (i.e., bicubic down-sampling), typically suffer from poor performance…

cs.CV2021

Image-to-Image Translation: Methods and Applications

Yingxue Pang, Jianxin Lin, Tao Qin +1

Image-to-image translation (I2I) aims to transfer images from a source domain to a target domain while preserving the content representations. I2I has drawn increasing attention an…

eess.IV20203 cited

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…

cs.CV202020 cited

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…

cs.CV2020

TuiGAN: Learning Versatile Image-to-Image Translation with Two Unpaired Images

Jianxin Lin, Yingxue Pang, Yingce Xia +2

An unsupervised image-to-image translation (UI2I) task deals with learning a mapping between two domains without paired images. While existing UI2I methods usually require numerous…