5 papers
PhysVista: Benchmarking Physical Intelligence in VLMs via a Perception-Reasoning-Assessment Loop
Xinge Peng, Yiting Lu, Tianwu Zhi +4
Vision-Language Models (VLMs) have shown strong multimodal reasoning capabilities, yet whether they truly capture the physical consistency underlying real-world dynamics remains un…
LoViF 2026 Challenge on Human-oriented Semantic Image Quality Assessment: Methods and Results
Xin Li, Daoli Xu, Wei Luo +27
This paper reviews the LoViF 2026 Challenge on Human-oriented Semantic Image Quality Assessment. This challenge aims to raise a new direction, i.e., how to evaluate the loss of sem…
Self-Evolving Vision-Language Models for Image Quality Assessment via Voting and Ranking
Wen Wen, Tianwu Zhi, Kanglong Fan +6
Improving vision-language models (VLMs) in the post-training stage typically relies on supervised fine-tuning or reinforcement learning, methods that necessitate costly, human-anno…
Context and Pixel Aware Large Language Model for Video Quality Assessment
Wen Wen, Yaohong Wu, Yue Sheng +3
Video quality assessment (VQA) is a challenging research topic with broad applications. Traditional hand-crafted and discriminative learning-based VQA models mainly focus on pixel-…
An Ensemble Approach to Short-form Video Quality Assessment Using Multimodal LLM
Wen Wen, Yilin Wang, Neil Birkbeck +1
The rise of short-form videos, characterized by diverse content, editing styles, and artifacts, poses substantial challenges for learning-based blind video quality assessment (BVQA…