ali-vilab/AnyDoor

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

4238 stars · 371 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

AnyDoor is the official implementation of a diffusion-based model that teleports target objects into new scenes at user-specified locations with zero-shot generalization. It provides training, inference, and demo code along with pretrained checkpoints for object-level image customization.

Use cases

• move an object into a new background image
• swap objects between two photos
• compose multiple subjects into one scene
• virtual try-on preserving clothing textures
• place a product photo into a marketing scene
• transfer logos or text onto objects

When to choose

• you need zero-shot object placement in images without per-object fine-tuning
• you want to preserve object texture details while adapting lighting and pose
• you need a baseline for virtual try-on or object moving research

When to avoid

• you need simple whole-image style transfer or text-to-image generation without object control
• you lack a GPU or cannot download large checkpoints
• you need a production-ready polished application rather than research code

Facets

library · maturity active

image-processing machine-learning deep-learning image-processing artificial-intelligence computer-vision python cross-platform diffusion-models image-generation image-editing zero-shot object-composition virtual-try-on research-code gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="ali-vilab/AnyDoor")