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20172026
most citedA Deep Learning based No-reference Quality Assessment Model for UGC Videos

240 citations · 830 across the 189 of their papers we have counts for

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151 papers · 1 filter

cs.CV2026

Invisible in Space, Visible in Time: Motion Vision CAPTCHA against GUI Agents

Zeyu Zhang, Dingyi Rong, Zijian Chen +3

Most existing visual CAPTCHAs remain spatially solvable: the required information is exposed by static appearance, local structure, and interface state. This assumption is weakened…

cs.CV2026

LLaVA-Assessor: Building the Foundation LMM For Visual Quality Assessment

Ziheng Jia, Zicheng Zhang, Jiaying Qian +2

Aligning with the human visual system~(HVS) in perceiving and evaluating the quality of visual signals is a central objective of machine-vision-based visual quality assessment syst…

cs.CV2026

Emo-Bench: A Scalable Benchmark for Multimodal Evoked and Expressed Emotion Understanding via Bayesian Pairwise Alignment

Lancheng Gao, Ziheng Jia, Shengyan Li +4

Understanding both expressed and evoked emotions is critical for multimodal large language models (MLLMs) to achieve comprehensive affect-aware interactions. However, existing benc…

cs.CV2026

Visual Distortion Detection in UGC Images Using Large Multimodal Models

Ziheng Jia, Yingji Liang, Jiaying Qian +1

The localized depiction of perceptual quality has long been a crucial, yet underexplored, challenge in image quality assessment (IQA). Existing approaches based on large multimodal…

cs.CV2026

MIEScore: Human-Aligned Evaluation for Multi-Source Image Editing

Zitong Xu, Huiyu Duan, Xinyun Zhang +7

Recent advances in unified multimodal models have significantly improved text-guided image editing abilities. In particular, models such as Nano-Banana-Pro and GPT-Image-2 demonstr…

cs.CV2026

Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model

Sijing Wu, Yunhao Li, Huiyu Duan +4

AI-generated human-centric videos play a crucial role in a wide range of modern applications. However, they often suffer from quality issues and semantic mismatches, underscoring t…