activity
20182024
most citedAIM 2019 Challenge on Constrained Super-Resolution: Methods and Results

19 citations · 105 across the 17 of their papers we have counts for

collaborators

26 papers

cs.CV2024

NTIRE 2024 Challenge on Stereo Image Super-Resolution: Methods and Results

Longguang Wang, Yulan Guo, Juncheng Li +6

This paper summarizes the 3rd NTIRE challenge on stereo image super-resolution (SR) with a focus on new solutions and results. The task of this challenge is to super-resolve a low-…

cs.CV20227 cited

Revisiting Random Channel Pruning for Neural Network Compression

Yawei Li, Kamil Adamczewski, Wen Li +3

Channel (or 3D filter) pruning serves as an effective way to accelerate the inference of neural networks. There has been a flurry of algorithms that try to solve this practical pro…

cs.CV2022

NTIRE 2022 Challenge on Stereo Image Super-Resolution: Methods and Results

Longguang Wang, Yulan Guo, Yingqian Wang +3

In this paper, we summarize the 1st NTIRE challenge on stereo image super-resolution (restoration of rich details in a pair of low-resolution stereo images) with a focus on new sol…

cs.AR202111 cited

MFAGAN: A Compression Framework for Memory-Efficient On-Device Super-Resolution GAN

Wenlong Cheng, Mingbo Zhao, Zhiling Ye +1

Generative adversarial networks (GANs) have promoted remarkable advances in single-image super-resolution (SR) by recovering photo-realistic images. However, high memory consumptio…

eess.IV2021

NTIRE 2021 Challenge on Perceptual Image Quality Assessment

Jinjin Gu, Haoming Cai, Chao Dong +47

This paper reports on the NTIRE 2021 challenge on perceptual image quality assessment (IQA), held in conjunction with the New Trends in Image Restoration and Enhancement workshop (…

cs.CV2021

Improving Facial Attribute Recognition by Group and Graph Learning

Zhenghao Chen, Shuhang Gu, Feng Zhu +2

Exploiting the relationships between attributes is a key challenge for improving multiple facial attribute recognition. In this work, we are concerned with two types of correlation…