9 papers
Incantation: Natural Language as the Action Interface for Multi-Entity Video World Models
Shangwen Zhu, Qianyu Peng, Zhao Pu +12
Modern interactive video world models have achieved impressive visual fidelity, yet lack fine-grained multi-entity control and cross-entity, cross-world generalization. We trace th…
Accelerating Diffusion Sampling via Exploiting Local Transition Coherence
Shangwen Zhu, Han Zhang, Zhantao Yang +4
Text-based diffusion models have made significant breakthroughs in generating high-quality images and videos from textual descriptions. However, the lengthy sampling time of the de…
TIE: Time Interval Encoding for Video Generation over Events
Zhilei Shu, Shangwen Zhu, Zihang Liang +10
Director-style prompting, robotic action prediction, and interactive video agents demand temporal grounding over concurrent events -- a regime in which 68% of general clips and ove…
Towards Interpretable Visual Decoding with Attention to Brain Representations
Pinyuan Feng, Hossein Adeli, Wenxuan Guo +3
Recent work has demonstrated that complex visual stimuli can be decoded from human brain activity using deep generative models, offering new ways to probe how the brain represents…
MAMBO-G: Magnitude-Aware Mitigation for Boosted Guidance
Shangwen Zhu, Qianyu Peng, Zhilei Shu +9
High-fidelity text-to-image and text-to-video generation typically relies on Classifier-Free Guidance (CFG), but achieving optimal results often demands computationally expensive s…
AnyView: Synthesizing Any Novel View in Dynamic Scenes
Basile Van Hoorick, Dian Chen, Shun Iwase +7
Modern generative video models excel at producing convincing, high-quality outputs, but struggle to maintain multi-view and spatiotemporal consistency in highly dynamic real-world…