5 papers
Multimodal Priors-Augmented Text-Driven 3D Human-Object Interaction Generation
Yin Wang, Ziyao Zhang, Zhiying Leng +4
We address the challenging task of text-driven 3D human-object interaction (HOI) motion generation. Existing methods primarily rely on a direct text-to-HOI mapping, which suffers f…
Dynamic Worlds, Dynamic Humans: Generating Virtual Human-Scene Interaction Motion in Dynamic Scenes
Yin Wang, Zhiying Leng, Haitian Liu +3
Scenes are continuously undergoing dynamic changes in the real world. However, existing human-scene interaction generation methods typically treat the scene as static, which deviat…
Fine-grained text-driven dual-human motion generation via dynamic hierarchical interaction
Mu Li, Yin Wang, Zhiying Leng +3
Human interaction is inherently dynamic and hierarchical, where the dynamic refers to the motion changes with distance, and the hierarchy is from individual to inter-individual and…
MOST: Motion Diffusion Model for Rare Text via Temporal Clip Banzhaf Interaction
Yin Wang, Mu li, Zhiying Leng +2
We introduce MOST, a novel motion diffusion model via temporal clip Banzhaf interaction, aimed at addressing the persistent challenge of generating human motion from rare language…
Fg-T2M++: LLMs-Augmented Fine-Grained Text Driven Human Motion Generation
Yin Wang, Mu Li, Jiapeng Liu +4
We address the challenging problem of fine-grained text-driven human motion generation. Existing works generate imprecise motions that fail to accurately capture relationships spec…