This repo hosts the official implementation of the MAXIM models:

"MAXIM: Multi-Axis MLP for Image Processing". CVPR 2022 Oral.
Zhengzhong Tu, Hossein Talebi, Han Zhang, Feng Yang, Peyman Milanfar, Alan Bovik, and Yinxiao Li
Google Research, University of Texas at Austin

Disclaimer: This is not an officially supported Google product.

News:

• Jan 8, 2023: Released a pytorch implementation. Check it out here: maxim-pytorch.
• Oct 21, 2022: MAXIM models have been ported to TensorFlow by @sayakpaul. Check it out here: maxim-tf. He also created a couple of Hugging Face Spaces to allow users to quickly try out the different models:
  • Denoising
  • Low-light enhancement
  • Image retouching
  • Dehazing indoors
  • Dehazing outdoors
  • Image deraining
  • Image deblurring
• Sep 8, 2022: our Google AI blog covering both MaxViT and MAXIM is live.
• Apr 25, 2022: Added demos.
  • Colab demo by @deshwalmahesh
  • Replicate web demo .
• Jun 22, 2022: MAXIM selected as 1 of the best paper nomination!
• Mar 29, 2022: MAXIM selected for an oral presentation at CVPR 2022!
• Mar 28, 2022: initial push to Github.
• Mar 3, 2022: paper accepted to CVPR 2022!
• Jan 9, 2022: initial uploads to Arxiv

Try the web demo for Image Denoising, Deblurring, Deraining, Dehazing and Enhancement with customized input image here

Try the Colab here using

The original requirements file was quite permissive and I add to change it to make it work. If you run the original one, you might run into problems with Jax,ml-dtypes,and or Tensorflow. I updated the requirements by restricting the possible versions to make it work and adding Pillow.

Install dependencies:

Using pip:

pip install -r requirements.txt

Or Using uv:

uv add -r requirements.txt

Setup project:

Using pip:

pip install -e .

Or Using uv:

uv pip install -e

We provide the pre-trained models and visual results. Please contact us if you have any questions or requests.

First download corresponding checkpoints and then go ahead and run:

python3 maxim/run_eval.py --task Denoising --ckpt_path ${SIDD_CKPT_PATH} \
  --input_dir maxim/images/Denoising --output_dir maxim/images/Results --has_target=False

python3 maxim/run_eval.py --task Deblurring --ckpt_path ${GOPRO_CKPT_PATH} \
  --input_dir maxim/images/Deblurring --output_dir maxim/images/Results --has_target=False

python3 maxim/run_eval.py --task Deraining --ckpt_path ${RAIN13K_CKPT_PATH} \
  --input_dir maxim/images/Deraining --output_dir maxim/images/Results --has_target=False

python3 maxim/run_eval.py --task Deraining --ckpt_path ${RAINDROP_CKPT_PATH} \
  --input_dir maxim/images/Deraining --output_dir maxim/images/Results --has_target=False

python3 maxim/run_eval.py --task Dehazing --ckpt_path ${REDISE_INDOOR_CKPT_PATH} \
  --input_dir maxim/images/Dehazing --output_dir maxim/images/Results --has_target=False

python3 maxim/run_eval.py --task Dehazing --ckpt_path ${REDISE_OUTDOOR_CKPT_PATH} \
  --input_dir maxim/images/Dehazing --output_dir maxim/images/Results --has_target=False

python3 maxim/run_eval.py --task Enhancement --ckpt_path ${LOL_CKPT_PATH} \
  --input_dir maxim/images/Enhancement --output_dir maxim/images/Results --has_target=False

python3 maxim/run_eval.py --task Enhancement --ckpt_path ${FIVEK_CKPT_PATH} \
  --input_dir maxim/images/Enhancement --output_dir maxim/images/Results --has_target=False

Image Denoising (click to expand)

Image Deblurring (click to expand)

Synthetic blur	Realistic blur

Image Deraining (click to expand)

Rain streak	Rain drop

Image Dehazing (click to expand)

Image Enhancement (click to expand)

Should you find this repository useful, please consider citing:

@article{tu2022maxim,
  title={MAXIM: Multi-Axis MLP for Image Processing},
  author={Tu, Zhengzhong and Talebi, Hossein and Zhang, Han and Yang, Feng and Milanfar, Peyman and Bovik, Alan and Li, Yinxiao},
  journal={CVPR},
  year={2022},
}

This repository is built on the vision_transformer and musiq repositories. Our work is also inspired by HiT, MPRNet, and HINet.