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AnyDoor: Zero-Shot Image Customization With Region-to-Region Reference.

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|April 25, 2025

Summary

This summary is machine-generated.

AnyDoor is a novel diffusion-based image generator that allows users to place objects into new scenes with precise control over location and shape. This versatile model achieves zero-shot generalization for diverse object-scene combinations without retraining.

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Area of Science:

Computer Vision
Artificial Intelligence
Machine Learning

Background:

Object insertion and manipulation in images are complex tasks.
Existing methods often require object-specific fine-tuning or struggle with generalization.
Controllable image generation with precise object placement remains a significant challenge.

Purpose of the Study:

To introduce AnyDoor, a diffusion-based image generation model for zero-shot object teleportation.
To enable precise control over object placement, shape, and integration into new scenes.
To develop a unified framework for object insertion, removal, and image variation.

Main Methods:

Leveraging DINOv2 for discriminative object identity feature extraction.
Complementing identity features with detail features for appearance consistency and local variations.
Utilizing video datasets to enhance model generalizability and robustness.
Extending the framework for region-to-region image referencing, unifying multiple generation tasks.

Main Results:

AnyDoor demonstrates effective zero-shot generalization across diverse object-scene combinations.
The model successfully teleports objects to specified locations with desired shapes.
A unified model handles object insertion, removal, and image variation without additional parameters.
Incorporation of masks, pose skeletons, and depth maps allows for more controllable generation.

Conclusions:

AnyDoor provides a powerful and versatile solution for controllable object manipulation in images.
The proposed method significantly advances the state-of-the-art in zero-shot image generation and object insertion.
The unified framework offers a flexible approach for various image editing and generation tasks.