MotionDreamer generates 3D animations from 2D video

Researchers have developed MotionDreamer, a diffusion-based framework capable of generating skeletal animations for 3D rigged shapes using 2D video as guidance. This method is designed to be category-agnostic, meaning it can animate a wide variety of 3D models regardless of their topology or morphology. To address the lack of diverse training data, a large dataset of approximately 20,000 3D models with animations was curated. MotionDreamer integrates texture and semantic attributes into its skeletal joint representations to accurately map visual motion cues to different 3D structures, achieving state-of-the-art results in 4D asset generation. AI

IMPACT Enables more efficient and versatile creation of animated 3D assets for various applications.

RANK_REASON This is a research paper describing a new method for generating 3D animations. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

• arXiv
• MotionDreamer

• paper
• product

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →