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20242026
most citedQuality-guided Skin Tone Enhancement for Portrait Photography

2 citations · 3 across the 11 of their papers we have counts for

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cs.CV2026

DPC-VQA: Decoupling Quality Perception and Residual Calibration for Video Quality Assessment

Xinyue Li, Shubo Xu, Zhichao Zhang +3

Recent multimodal large language models (MLLMs) have shown promising performance on video quality assessment (VQA) tasks. However, adapting them to new scenarios remains expensive…

cs.CV2026

FireRed-OCR Technical Report

Hao Wu, Haoran Lou, Xinyue Li +19

We present FireRed-OCR, a systematic framework to specialize general VLMs into high-performance OCR models. Large Vision-Language Models (VLMs) have demonstrated impressive general…

cs.CV2026

ELIQ: A Label-Free Framework for Quality Assessment of Evolving AI-Generated Images

Xinyue Li, Zhiming Xu, Min Tang +5

Generative text-to-image models are advancing at an unprecedented pace, continuously shifting the perceptual quality ceiling and rendering previously collected labels unreliable fo…

cs.CV2026

Decoupling Perception and Calibration: Label-Efficient Image Quality Assessment Framework

Xinyue Li, Zhichao Zhang, Zhiming Xu +4

Recent multimodal large language models (MLLMs) have demonstrated strong capabilities in image quality assessment (IQA) tasks. However, adapting such large-scale models is computat…

cs.CV2026

Q-Bench-Portrait: Benchmarking Multimodal Large Language Models on Portrait Image Quality Perception

Sijing Wu, Yunhao Li, Zicheng Zhang +5

Recent advances in multimodal large language models (MLLMs) have demonstrated impressive performance on existing low-level vision benchmarks, which primarily focus on generic image…

cs.CV2025

VQualA 2025 Challenge on Visual Quality Comparison for Large Multimodal Models: Methods and Results

Hanwei Zhu, Haoning Wu, Zicheng Zhang +26

This paper presents a summary of the VQualA 2025 Challenge on Visual Quality Comparison for Large Multimodal Models (LMMs), hosted as part of the ICCV 2025 Workshop on Visual Quali…