20 citations · 179 across the 97 of their papers we have counts for
7 papers · 2 filters
DecFlowEdit: Self-Localized Flow-based Image Editing via Guidance Decoupling
Zheyuan Zhan, Can Wang, Jiawei Chen +4
Flow-based image editing (FlowEdit) enables inversion-free semantic changes through the difference between source and target velocities. In this paper, we observe that FlowEdit's d…
PIVOT: Physics-Grounded Verification for AI-Generated Audio-Video Detection
Bo Zheng, Kangran Zhao, Xiaoyu Zhang +7
As generative models continue to advance, AI-generated content (AIGC) is becoming increasingly realistic, weakening the artifact cues commonly exploited by existing detectors. Neve…
Distributed Implicit Harm: A Compositional Safety Blind Spot in MLLM-Based Video Moderation
Ruotong Wang, Zihao Zhu, Siwei Lyu +2
Despite their growing use in video moderation, multimodal large language models (MLLMs) exhibit a compositional safety blind spot: videos composed of seemingly benign components ca…
LoCC: Detection and Localization of Lip-Syncing Deepfakes via Counterfactual Frame Consistency
Soumyya Kanti Datta, Shan Jia, Siwei Lyu
Lip-syncing deepfakes are among the most challenging forms of manipulated media because their artifacts are localized almost exclusively to the mouth region and evolve dynamically…
Conditioning Matters: Stabilizing Inversion and Attention in Diffusion Image Editing
Zheyuan Zhan, Hongchen Li, Can Wang +6
Inversion-based image editing offers flexible and training-free control but still struggles with inversion accuracy and the trade-off between editing fidelity and background preser…
BrandFusion: A Multi-Agent Framework for Seamless Brand Integration in Text-to-Video Generation
Zihao Zhu, Ruotong Wang, Siwei Lyu +2
The rapid advancement of text-to-video (T2V) models has revolutionized content creation, yet their commercial potential remains largely untapped. We introduce, for the first time,…
Analyzing and Improving Fast Sampling of Text-to-Image Diffusion Models
Zhenyu Zhou, Defang Chen, Siwei Lyu +2
Text-to-image diffusion models have achieved unprecedented success but still struggle to produce high-quality results under limited sampling budgets. Existing training-free samplin…