9 papers
RoMo: A Large-Scale, Richly Organized Dataset and Semantic Taxonomy for Human Motion Generation
Jiahao Zhang, Joseph Liu, Young-Yoon Lee +9
Success in generative modeling across language, image, and video demonstrates that large, well-curated datasets are the key driver for building capable models. 3D Human motion, how…
SMP: Reusable Score-Matching Motion Priors for Physics-Based Character Control
Yuxuan Mu, Ziyu Zhang, Yi Shi +9
Data-driven motion priors that can guide agents toward producing naturalistic behaviors play a pivotal role in creating life-like virtual characters. Adversarial imitation learning…
BeyondMimic: From Motion Tracking to Versatile Humanoid Control via Guided Diffusion
Qiayuan Liao, Takara E. Truong, Xiaoyu Huang +4
The human-like form of humanoid robots positions them uniquely to achieve the agility and versatility in motor skills that humans possess. Learning from human demonstrations offers…
HOIDiNi: Human-Object Interaction through Diffusion Noise Optimization
Roey Ron, Guy Tevet, Haim Sawdayee +1
We present HOIDiNi, a text-driven diffusion framework for synthesizing realistic and plausible human-object interaction (HOI). HOI generation is extremely challenging since it indu…
Generating Detailed Character Motion from Blocking Poses
Purvi Goel, Guy Tevet, C. K. Liu +1
We focus on the problem of using generative diffusion models for the task of motion detailing: converting a rough version of a character animation, represented by a sparse set of c…
Express4D: Expressive, Friendly, and Extensible 4D Facial Motion Generation Benchmark
Yaron Aloni, Rotem Shalev-Arkushin, Yonatan Shafir +3
Dynamic facial expression generation from natural language is a crucial task in Computer Graphics, with applications in Animation, Virtual Avatars, and Human-Computer Interaction.…