IMPUS: Image Morphing with Perceptually-Uniform Sampling Using Diffusion Models

Official repository of IMPUS: Image Morphing with Perceptually-Uniform Sampling Using Diffusion Models, ICLR 2024.

This repository is under reconstruction...

Paper

Environment setup

This code was tested with Python 3.9, Pytorch 1.13.1. based on huggingface / diffusers. The pretrained diffusion model is from Stable Diffusion v-1-4. Install package using requirements.txt by pip install -r requirements.txt.

The code requires at least 14GB VRAM.

Quickstart

Both training and inference for IMPUS are available at IMPUS.ipynb. Images in the notebook is for simple demo (replace with high resolution image generate better results), we will update with more examples later.

Morphing by command line

run_morph.py takes command line arguments to generate morphing outputs. It requires path of directory for saving image, two image paths and a prompt for morphing two images.

python run_morph.py --dir <saved_dir_path> --input_image_1 <img_path_1> --input_image_2 <img_path_2> --prompt <prompt_for_morphing>

Reference

to do: add code reference

Citation

@inproceedings{
yang2024impus,
title={{IMPUS}: Image Morphing with Perceptually-Uniform Sampling Using Diffusion Models},
author={Zhaoyuan Yang and Zhengyang Yu and Zhiwei Xu and Jaskirat Singh and Jing Zhang and Dylan Campbell and Peter Tu and Richard Hartley},
booktitle={The Twelfth International Conference on Learning Representations},
year={2024},
url={https://openreview.net/forum?id=gG38EBe2S8}
}