2 citations · 2 across the 8 of their papers we have counts for
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iDiff: Interpretable Difference-aware Framework for Pairwise Image Quality Assessment
Xinli Yue, JianHui Sun, Tao Shao +3
Pairwise image quality assessment (IQA) in professional photography requires a model not only to identify the preferred image between two candidates, but also to provide convincing…
NTIRE 2026 The 3rd Restore Any Image Model (RAIM) Challenge: Professional Image Quality Assessment (Track 1)
Guanyi Qin, Jie Liang, Bingbing Zhang +50
In this paper, we present an overview of the NTIRE 2026 challenge on the 3rd Restore Any Image Model in the Wild, specifically focusing on Track 1: Professional Image Quality Asses…
iDETEX: Empowering MLLMs for Intelligent DETailed EXplainable IQA
Zhaoran Zhao, Xinli Yue, Jianhui Sun +5
Image Quality Assessment (IQA) has progressed from scalar quality prediction to more interpretable, human-aligned evaluation paradigms. In this work, we address the emerging challe…
NTIRE 2025 challenge on Text to Image Generation Model Quality Assessment
Shuhao Han, Haotian Fan, Fangyuan Kong +112
This paper reports on the NTIRE 2025 challenge on Text to Image (T2I) generation model quality assessment, which will be held in conjunction with the New Trends in Image Restoratio…
Instruction-augmented Multimodal Alignment for Image-Text and Element Matching
Xinli Yue, JianHui Sun, Junda Lu +6
With the rapid advancement of text-to-image (T2I) generation models, assessing the semantic alignment between generated images and text descriptions has become a significant resear…
Advancing Video Quality Assessment for AIGC
Xinli Yue, Jianhui Sun, Han Kong +9
In recent years, AI generative models have made remarkable progress across various domains, including text generation, image generation, and video generation. However, assessing th…
Revisiting Video Quality Assessment from the Perspective of Generalization
Xinli Yue, Jianhui Sun, Liangchao Yao +8
The increasing popularity of short video platforms such as YouTube Shorts, TikTok, and Kwai has led to a surge in User-Generated Content (UGC), which presents significant challenge…
Revisiting Adversarial Training under Long-Tailed Distributions
Xinli Yue, Ningping Mou, Qian Wang +1
Deep neural networks are vulnerable to adversarial attacks, often leading to erroneous outputs. Adversarial training has been recognized as one of the most effective methods to cou…