activity
20192021
most citedAIM 2020 Challenge on Real Image Super-Resolution: Methods and Results

20 citations · 37 across the 6 of their papers we have counts for

collaborators

8 papers

cs.CV2021

A Dataset and Method for Hallux Valgus Angle Estimation Based on Deep Learing

Ningyuan Xu, Jiayan Zhuang, Yaojun Wu +1

Angular measurements is essential to make a resonable treatment for Hallux valgus (HV), a common forefoot deformity. However, it still depends on manual labeling and measurement, w…

eess.IV2020

Learned Block-based Hybrid Image Compression

Yaojun Wu, Xin Li, Zhizheng Zhang +2

Recent works on learned image compression perform encoding and decoding processes in a full-resolution manner, resulting in two problems when deployed for practical applications. F…

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.CV20208 cited

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…

eess.IV20203 cited

Learned Video Compression with Feature-level Residuals

Runsen Feng, Yaojun Wu, Zongyu Guo +3

In this paper, we present an end-to-end video compression network for P-frame challenge on CLIC. We focus on deep neural network (DNN) based video compression, and improve the curr…