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20222024
most citedQ-Align: Teaching LMMs for Visual Scoring via Discrete Text-Defined Levels

33 citations · 59 across the 13 of their papers we have counts for

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11 papers · 1 filter

cs.CV2024

Towards Open-ended Visual Quality Comparison

Haoning Wu, Hanwei Zhu, Zicheng Zhang +11

Comparative settings (e.g. pairwise choice, listwise ranking) have been adopted by a wide range of subjective studies for image quality assessment (IQA), as it inherently standardi…

cs.CV202333 cited

Q-Align: Teaching LMMs for Visual Scoring via Discrete Text-Defined Levels

Haoning Wu, Zicheng Zhang, Weixia Zhang +11

The explosion of visual content available online underscores the requirement for an accurate machine assessor to robustly evaluate scores across diverse types of visual contents. W…

cs.CV20232 cited

Q-Instruct: Improving Low-level Visual Abilities for Multi-modality Foundation Models

Haoning Wu, Zicheng Zhang, Erli Zhang +11

Multi-modality foundation models, as represented by GPT-4V, have brought a new paradigm for low-level visual perception and understanding tasks, that can respond to a broad range o…

cs.CV20233 cited

Local Distortion Aware Efficient Transformer Adaptation for Image Quality Assessment

Kangmin Xu, Liang Liao, Jing Xiao +4

Image Quality Assessment (IQA) constitutes a fundamental task within the field of computer vision, yet it remains an unresolved challenge, owing to the intricate distortion conditi…

cs.CV20235 cited

TOPIQ: A Top-down Approach from Semantics to Distortions for Image Quality Assessment

Chaofeng Chen, Jiadi Mo, Jingwen Hou +5

Image Quality Assessment (IQA) is a fundamental task in computer vision that has witnessed remarkable progress with deep neural networks. Inspired by the characteristics of the hum…

cs.CV20232 cited

NTIRE 2023 Quality Assessment of Video Enhancement Challenge

Xiaohong Liu, Xiongkuo Min, Wei Sun +69

This paper reports on the NTIRE 2023 Quality Assessment of Video Enhancement Challenge, which will be held in conjunction with the New Trends in Image Restoration and Enhancement W…