# ali-vilab/UniAnimate

Code for SCIS-2025 Paper "UniAnimate: Taming Unified Video Diffusion Models for Consistent Human Image Animation".

Repository: https://github.com/ali-vilab/UniAnimate
Canonical: https://ross.abutalabs.com/products/unianimate
Homepage: https://unianimate.github.io/
Language: Python
License Family: other
Topics: dance-generation, video-generation, human-image-animation
Last push: 2025-04-15T03:52:14+00:00

## Health v2 (maintenance only)
Score: 31/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 16, release rhythm 35, longevity 58
- inputs: {"age_days": 821, "days_push": 505, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1189, forks 62 (observed 2026-08-28T04:03:55.426393+00:00)

## What it is
UniAnimate is the official code for a research paper on animating a reference human image into a video that follows a driving pose sequence, using unified video diffusion models. It supports long-term video generation (up to about a minute) via first-frame conditioning and a state-space-model temporal architecture.

## Use cases
- animate a photo of a person with a driving pose sequence
- generate dance videos from a reference image
- create long consistent human animation videos
- research on video diffusion models for human animation
- pose-driven character video synthesis

## When to choose
- you need research-grade human image animation with pose control
- you want to generate long videos of a person from a single image
- you have a GPU and want to experiment with video diffusion models

## When to avoid
- you need a production-ready product with a polished UI
- you have no GPU available
- you need a permissively licensed library for commercial use (no license is provided)

## Facets
- artifact type: library
- maturity: active
- function: video-processing, deep-learning, image-processing, machine-learning
- domain: computer-vision, deep-learning, artificial-intelligence
- platform: python
- tags: human-image-animation, video-diffusion, pose-driven-animation, dance-generation, video-generation, research-code, video, gpu, linux

## Member repositories
- ali-vilab/UniAnimate (main) score 31

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:55.426393+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:23:07.720458+00:00, confidence not recorded.
  - readme: https://github.com/ali-vilab/UniAnimate (fetched 2026-08-28T04:03:55.426393+00:00, sha 5e8e21e14c15)
  - homepage: https://unianimate.github.io/ (fetched 2026-08-29T12:30:37.591715+00:00, sha bb7ea7c2d7e0)
- Data as of 2026-08-30T08:39:29.467469+00:00.