Composer

Official repo for Composer: Creative and Controllable Image Synthesis with Composable Conditions.

See Project Page for more examples.

Composer is a large (5 billion parameters) controllable diffusion model trained on billions of (text, image) pairs. It can exponentially expand the control space through composition, leading to an enormous number of ways to generate and manipulate images, i.e., making the infinite use of finite means.

TODO

Release training and inference code.
Release pretrained models.
Release Gradio UI.
A light-weighted Latent-Composer built upon Stable Diffusion 2.1.

Composition Results

Composition of text and depth.

Composition of masked image and text.

Composition of sketch, depth and embedding (1).

Composition of sketch, depth and embedding (2).

Composition of text and palette.

Composition of embedding and palette.

Composition of intensity and palette.

Manipulation Results

Image variations when fixing sketch, depth, palette and/or embedding.

Image interpolations when fixing sketch, depth, segmentation map and/or palette.

Image reconfigurations (manipulating an image by directly modifying its elements).

Color interpolations.

Region-specific image editing.

Reformulation of Classical Tasks

Image translation.

Style transfer.

Pose transfer.

Virtual try-on.

BibTeX

@article{lhhuang2023composer,
  title={Composer: Creative and Controllable Image Synthesis with Composable Conditions},
  author={Huang, Lianghua and Chen, Di and Liu, Yu and Yujun, Shen and Zhao, Deli and Jingren, Zhou},
  booktitle={arXiv preprint arxiv:2302.09778},
  year={2023}
}

amul/composer