# AliaksandrSiarohin/first-order-model

This repository contains the source code for the paper First Order Motion Model for Image Animation

Repository: https://github.com/AliaksandrSiarohin/first-order-model
Canonical: https://ross.abutalabs.com/products/first-order-model
Homepage: https://aliaksandrsiarohin.github.io/first-order-model-website/
Language: Jupyter Notebook
License: MIT
License Family: permissive
Topics: deep-learning, image-animation, generative-model, motion-retargeting
Last push: 2024-11-14T03:16:41+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2457, "days_push": 657, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 15015, forks 3256 (observed 2026-08-28T04:11:09.061128+00:00)

## What it is
Official PyTorch/Jupyter implementation of the First Order Motion Model for image animation (NeurIPS 2019). It animates a static source image (e.g., a face or body) using motion transferred from a driving video, without object-specific annotations.

## Use cases
- animate a photo with motion from a driving video
- make a face talk using a video of someone else
- transfer facial expressions from video to a still image
- create deepfake-style talking head videos
- retarget motion from one person to another
- reproduce the First Order Motion Model paper results

## When to choose
- you want to animate a still image from a driving video using a proven research model
- you need pre-trained checkpoints for faces (VoxCeleb), fashion, or animated graphics
- you want a reproducible implementation of the NeurIPS 2019 paper

## When to avoid
- you need a production-ready or maintained product rather than research code
- you need articulated-object animation - the authors recommend their newer articulated-animation framework
- you need real-time animation or a polished user interface

## Facets
- artifact type: library
- maturity: maintenance
- function: deep-learning, image-processing, video-processing, machine-learning
- domain: deep-learning, computer-vision, image-processing
- platform: python
- tags: image-animation, motion-transfer, deepfake, generative-model, face-animation, neurips-2019, research-code, video, linux, gpu

## Member repositories
- AliaksandrSiarohin/first-order-model (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:09.061128+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 2026-08-29T17:06:46.383887+00:00, confidence not recorded.
  - readme: https://github.com/AliaksandrSiarohin/first-order-model (fetched 2026-08-28T04:11:09.061128+00:00, sha 842faa6c3bf8)
  - homepage: https://aliaksandrsiarohin.github.io/first-order-model-website/ (fetched 2026-08-29T08:04:43.870918+00:00, sha de8a8b41e44f)
- Data as of 2026-08-30T08:39:29.467469+00:00.