Mix-DDPM-Pytorch

Mix-DDPM: Enhancing Diffusion Models through Fitting Mixture Noise with Global Stochastic Offset
Hanzhang Wang, Deming Zhai, Xiong Zhou, Junjun Jiang, Xianming Liu.
ACM Transactions on Multimedia Computing, Communications, and Applications (ToMM), 2024.

Reference

Citation:

@article{wang2024mix,
  title={Mix-DDPM: Enhancing Diffusion Models through Fitting Mixture Noise with Global Stochastic Offset},
  author={Wang, Hanzhang and Zhai, Deming and Zhou, Xiong and Jiang, Junjun and Liu, Xianming},
  journal={ACM Transactions on Multimedia Computing, Communications and Applications},
  publisher={ACM New York, NY}
}

Installation

Clone this repository and navigate to it in your terminal. Then run:

pip install -e .

This should install the improved_diffusion python package that the scripts depend on.

Preparing Data

The training code reads images from a directory of image files. In the datasets folder, we have provided instructions/scripts for preparing these directories for ImageNet, LSUN bedrooms, and CIFAR-10.

Training

run bash file in train_sh

Inference

run bash file in test_sh