35 citations · 56 across the 8 of their papers we have counts for
7 papers · 1 filter
Assessor360: Multi-sequence Network for Blind Omnidirectional Image Quality Assessment
Tianhe Wu, Shuwei Shi, Haoming Cai +4
Blind Omnidirectional Image Quality Assessment (BOIQA) aims to objectively assess the human perceptual quality of omnidirectional images (ODIs) without relying on pristine-quality…
Mitigating Artifacts in Real-World Video Super-Resolution Models
Liangbin Xie, Xintao Wang, Shuwei Shi +3
The recurrent structure is a prevalent framework for the task of video super-resolution, which models the temporal dependency between frames via hidden states. When applied to real…
Rethinking Alignment in Video Super-Resolution Transformers
Shuwei Shi, Jinjin Gu, Liangbin Xie +3
The alignment of adjacent frames is considered an essential operation in video super-resolution (VSR). Advanced VSR models, including the latest VSR Transformers, are generally equ…
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…
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…
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…
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…