humanaigc/outfitanyone

★ 5,980Audience · researcherComplexity · 1/5Setup · easy

Mindmap

mindmap
  root((OutfitAnyone))
    What it does
      Virtual try-on
      Clothing visualization
    How it works
      Generative AI model
      Clothing compositing
    Access points
      Hugging Face demo
      ModelScope demo
    Companion project
      AnimateAnyone
    Audience
      Fashion researchers
      Design explorers

mindmap root((OutfitAnyone)) What it does Virtual try-on Clothing visualization How it works Generative AI model Clothing compositing Access points Hugging Face demo ModelScope demo Companion project AnimateAnyone Audience Fashion researchers Design explorers

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Things people build with this

USE CASE 1

Preview what a clothing item looks like on a person using the Hugging Face hosted demo.

USE CASE 2

Explore the OutfitAnyone paper to understand the AI approach to virtual clothing try-on.

USE CASE 3

Combine OutfitAnyone with AnimateAnyone to view clothing on a moving AI figure.

Getting it running

Difficulty · easy Time to first run · 5min

No local setup available, the demo only accepts clothing images, not real personal photos, due to misuse prevention restrictions.

In plain English

OutfitAnyone is an AI research project from Alibaba Group's Institute for Intelligent Computing that lets you see what a piece of clothing would look like on a person without physically trying it on. You provide a clothing image, and the system composites it onto a person using a generative AI model, producing a realistic-looking result. The current public demo, available on Hugging Face and on ModelScope for users in China, only accepts clothing images as input. The people shown in the demo outputs are pre-generated AI figures rather than real uploaded photos. The README notes this restriction is in place to prevent misuse of real personal photos. The project is research-level work published as an academic paper on arXiv. The repository accompanies that paper and provides access to a demo rather than a full self-hosted codebase for running locally. There is also a companion demo combining OutfitAnyone with a separate project called AnimateAnyone, which adds motion to the try-on results. The README is short and does not include installation instructions or model weights. It primarily links to the project page, the paper, and the hosted demos. If you want to try the system, the Hugging Face Space is the most accessible entry point.

Copy-paste prompts

Prompt 1

I have a product clothing image. Using the OutfitAnyone Hugging Face demo, how do I see what it looks like worn on a figure?

Prompt 2

Explain the technique OutfitAnyone uses to composite clothing onto a person image using a generative AI model.

Prompt 3

Where can I access the OutfitAnyone demo in China, and what are the input restrictions for the current public version?

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