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20232026
most citedCan Large Models Fool the Eye? A New Turing Test for Biological Animation

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cs.CV2026

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…

cs.CV2026

QualiRAG: Retrieval-Augmented Generation for Visual Quality Understanding

Linhan Cao, Wei Sun, Weixia Zhang +6

Visual quality assessment (VQA) is increasingly shifting from scalar score prediction toward interpretable quality understanding -- a paradigm that demands \textit{fine-grained spa…

cs.CV2026

KidVis: Do Multimodal Large Language Models Possess the Visual Perceptual Capabilities of a 6-Year-Old?

Xianfeng Wang, Kaiwei Zhang, Qi Jia +3

While Multimodal Large Language Models (MLLMs) have demonstrated impressive proficiency in high-level reasoning tasks, such as complex diagrammatic interpretation, it remains an op…

cs.CV2025

ManipShield: A Unified Framework for Image Manipulation Detection, Localization and Explanation

Zitong Xu, Huiyu Duan, Xiaoyu Wang +6

With the rapid advancement of generative models, powerful image editing methods now enable diverse and highly realistic image manipulations that far surpass traditional deepfake te…

cs.CV2025

VQualA 2025 Challenge on Engagement Prediction for Short Videos: Methods and Results

Dasong Li, Sizhuo Ma, Hang Hua +40

This paper presents an overview of the VQualA 2025 Challenge on Engagement Prediction for Short Videos, held in conjunction with ICCV 2025. The challenge focuses on understanding a…

cs.CV20251 cited

Can Large Models Fool the Eye? A New Turing Test for Biological Animation

Zijian Chen, Lirong Deng, Zhengyu Chen +5

Evaluating the abilities of large models and manifesting their gaps are challenging. Current benchmarks adopt either ground-truth-based score-form evaluation on static datasets or…