most citedMANIQA: Multi-dimension Attention Network for No-Reference Image Quality Assessment

3 citations · 5 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2022

NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video: Dataset, Methods and Results

Ren Yang, Radu Timofte, Meisong Zheng +75

This paper reviews the NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video. In this challenge, we proposed the LDV 2.0 dataset, which includes the…

cs.CV20221 cited

Attentions Help CNNs See Better: Attention-based Hybrid Image Quality Assessment Network

Shanshan Lao, Yuan Gong, Shuwei Shi +5

Image quality assessment (IQA) algorithm aims to quantify the human perception of image quality. Unfortunately, there is a performance drop when assessing the distortion images gen…

cs.CV20223 cited

MANIQA: Multi-dimension Attention Network for No-Reference Image Quality Assessment

Sidi Yang, Tianhe Wu, Shuwei Shi +5

No-Reference Image Quality Assessment (NR-IQA) aims to assess the perceptual quality of images in accordance with human subjective perception. Unfortunately, existing NR-IQA method…

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.CV20211 cited

Region-Adaptive Deformable Network for Image Quality Assessment

Shuwei Shi, Qingyan Bai, Mingdeng Cao +4

Image quality assessment (IQA) aims to assess the perceptual quality of images. The outputs of the IQA algorithms are expected to be consistent with human subjective perception. In…