# showlab/MotionDirector

[ECCV 2024 Oral] MotionDirector: Motion Customization of Text-to-Video Diffusion Models.

Repository: https://github.com/showlab/MotionDirector
Canonical: https://ross.abutalabs.com/products/motiondirector
Homepage: https://showlab.github.io/MotionDirector/
Language: Python
License: Apache-2.0
License Family: permissive
Topics: diffusion-models, text-to-motion, text-to-video, text-to-video-generation, video-generation, motion-customization
Last push: 2024-08-21T03:51:01+00:00

## Health v2 (maintenance only)
Score: 27/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 75
- inputs: {"age_days": 1056, "days_push": 742, "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 1050, forks 62 (observed 2026-08-28T04:03:22.836502+00:00)

## What it is
MotionDirector is a research library for customizing text-to-video diffusion models to generate videos with desired motions from a small set of reference clips. It uses a dual-path LoRA architecture and appearance-debiased temporal loss to decouple motion learning from appearance.

## Use cases
- generate videos with a specific motion from reference clips
- customize text-to-video diffusion models with LoRA
- mix appearance from one video with motion from another
- animate a single image with a customized motion
- create videos with prescribed camera movements
- research on motion customization for video diffusion

## When to choose
- you need to teach a video diffusion model a specific motion concept
- you want decoupled control over appearance and motion in generated videos
- you are reproducing or building on ECCV 2024 motion customization research

## When to avoid
- you need production-grade video generation without training
- you lack a GPU or cannot run diffusion model fine-tuning
- you only need simple text-to-video generation without motion customization

## Facets
- artifact type: library
- maturity: active
- function: machine-learning, deep-learning, video-processing, image-processing
- domain: deep-learning, artificial-intelligence, image-processing
- platform: python
- tags: diffusion-models, text-to-video, motion-customization, lora, eccv-2024, video-generation, research, video, gpu, linux, docker

## Member repositories
- showlab/MotionDirector (main) score 27

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:22.836502+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 2026-08-30T07:00:24.904554+00:00, confidence not recorded.
  - readme: https://github.com/showlab/MotionDirector (fetched 2026-08-28T04:03:22.836502+00:00, sha e91640e85408)
  - homepage: https://showlab.github.io/MotionDirector/ (fetched 2026-08-29T13:01:59.743554+00:00, sha b18cc2b6c2c1)
- Data as of 2026-08-30T08:39:29.467469+00:00.