Francis-Rings/StableAnimator

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1430 stars · 102 forks observed · 2026-08-28

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

StableAnimator is an end-to-end ID-preserving video diffusion framework that animates a reference human image according to a sequence of poses, producing high-fidelity videos without face post-processing. It is a Python research codebase released at CVPR 2025, built on a video diffusion model with identity-consistency modules.

Use cases

• animate a photo with a pose sequence
• generate identity-preserving talking or dancing videos from an image
• create human image animation without face swapping post-processing
• run pose-driven video generation on a reference portrait
• research video diffusion identity consistency

When to choose

• you need high-fidelity ID-preserving human animation from a single image and pose sequence
• you want to avoid separate face-swap or face-restoration post-processing
• you have a GPU and want a state-of-the-art research model

When to avoid

• you need lightweight or CPU-only video generation
• you want general text-to-video rather than pose-conditioned human animation
• you lack GPU resources for diffusion inference

Facets

library · maturity active

video-processing image-processing deep-learning stable-diffusion machine-learning computer-vision deep-learning image-processing artificial-intelligence python video-diffusion human-image-animation identity-preservation pose-driven cvpr2025 face-consistency video gpu linux

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markdown · JSON · MCP: product_card(name="Francis-Rings/StableAnimator")