6 papers · 1 filter
Look Before You Judge: Training-Free Region Mining for Grounded and Explainable Deepfake Detection
Chia-Ling Chen, Yu-Ting Ta, Jian-Yu Jiang-Lin +8
Multimodal large language models (MLLMs) can explain deepfake verdicts in natural language, but such explanations are not necessarily visually grounded in the visual evidence under…
Attribute-Grounded Selective Reasoning for Artwork Emotion Understanding with Multimodal Large Language Models
Cheng Zhang, Yuer Liu, Zhiyu Zhou +2
Multimodal large language models (MLLMs) can produce fluent artwork emotion explanations, but they often suffer from attribute flooding: they enumerate many visible formal attribut…
PinpointQA: A Benchmark for Small Object-Centric Spatial Understanding in Indoor Videos
Zhiyu Zhou, Peilin Liu, Ruoxuan Zhang +4
Reliable embodied interaction in indoor environments requires agents to precisely localize small everyday objects from visual observations. Yet this fundamental capability remains…
TiViBench: Benchmarking Think-in-Video Reasoning for Video Generative Models
Harold Haodong Chen, Disen Lan, Wen-Jie Shu +10
The rapid evolution of video generative models has shifted their focus from producing visually plausible outputs to tackling tasks requiring physical plausibility and logical consi…
TriDF: Evaluating Perception, Detection, and Hallucination for Interpretable DeepFake Detection
Jian-Yu Jiang-Lin, Kang-Yang Huang, Ling Zou +11
Advances in generative modeling have made it increasingly easy to fabricate realistic portrayals of individuals, creating serious risks for security, communication, and public trus…
From Prompt to Progression: Taming Video Diffusion Models for Seamless Attribute Transition
Ling Lo, Kelvin C. K. Chan, Wen-Huang Cheng +1
Existing models often struggle with complex temporal changes, particularly when generating videos with gradual attribute transitions. The most common prompt interpolation approach…