lizhe00/AnimatableGaussians

Health v2 · maintenance only

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1093 stars · 80 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Official PyTorch implementation of the CVPR 2024 paper 'Animatable Gaussians', which learns pose-dependent Gaussian maps for high-fidelity animatable human avatar modeling from RGB videos. It combines 2D CNNs (StyleGAN-based) with 3D Gaussian splatting and a learned parametric template to create lifelike, animatable avatars.

Use cases

• create animatable 3d human avatars from rgb videos
• reconstruct high-fidelity 3d humans with gaussian splatting
• animate avatars with novel poses from motion capture data
• research on pose-dependent human appearance modeling
• build digital humans for games or virtual production
• compare against nerf-based avatar methods

When to choose

• you need photorealistic animatable human avatars from multi-view or rgb video
• you want to reproduce or extend a cvpr 2024 avatar modeling method
• you need pose-dependent garment detail that nerf-based methods struggle with
• you have gpu resources and smpl-based preprocessing pipelines available

When to avoid

• you need a production-ready avatar solution with a polished api or gui
• you lack multi-view rgb video or the required smpl/actorthq preprocessing assets
• you need real-time avatar animation on consumer hardware without a gpu
• you want a general-purpose 3d reconstruction tool not specific to humans

Facets

library · maturity active

machine-learning deep-learning image-processing graphics simulation computer-vision graphics machine-learning deep-learning python 3d-gaussian-splatting human-avatar animatable-avatar 3d-reconstruction cvpr-2024 research-code nerf-alternative linux gpu

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