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20242026
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cs.CV2026

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…

cs.CV2025

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…

cs.CV2025

Dance Like a Chicken: Low-Rank Stylization for Human Motion Diffusion

Haim Sawdayee, Chuan Guo, Guy Tevet +3

Text-to-motion generative models span a wide range of 3D human actions but struggle with nuanced stylistic attributes such as a "Chicken" style. Due to the scarcity of style-specif…

cs.CV2024

CLoSD: Closing the Loop between Simulation and Diffusion for multi-task character control

Guy Tevet, Sigal Raab, Setareh Cohan +5

Motion diffusion models and Reinforcement Learning (RL) based control for physics-based simulations have complementary strengths for human motion generation. The former is capable…

cs.CV2024

Monkey See, Monkey Do: Harnessing Self-attention in Motion Diffusion for Zero-shot Motion Transfer

Sigal Raab, Inbar Gat, Nathan Sala +5

Given the remarkable results of motion synthesis with diffusion models, a natural question arises: how can we effectively leverage these models for motion editing? Existing diffusi…

cs.CV2024

Flexible Motion In-betweening with Diffusion Models

Setareh Cohan, Guy Tevet, Daniele Reda +2

Motion in-betweening, a fundamental task in character animation, consists of generating motion sequences that plausibly interpolate user-provided keyframe constraints. It has long…