arXiv: https://arxiv.org/abs/2503.19062
This is the official implementation of AAAI 2025 paper "Color Transfer with Modulated Flows".
The paper was also presented at "Workshop SPIGM @ ICML 2024".
Please refer to the
- ModFlows_demo.ipynb to use the pretrained model for color transfer on your own images with the demo jupyter notebook
- ModFlows_demo_batched.ipynb to use the pretrained model for color transfer for large images
- HuggingFace for the model checkpoints
- src directory for models definitions
- generate_flows_v2 script for training the dataset of rectified flows
- train_encoder_v2 script for training the encoder
How to clone and download pre-trained weights:
git clone https://github.com/maria-larchenko/modflows.git
cd modflows; git clone https://huggingface.co/MariaLarchenko/modflows_color_encoder
Call python3 run_inference.py --help
to see a full list of arguments for inference.
Ctrl+C
cancels the execution.
If you use this code in your research, please cite our work:
@article{Larchenko_Lobashev_Guskov_Palyulin_2025, title={Color Transfer with Modulated Flows}, volume={39}, url={https://ojs.aaai.org/index.php/AAAI/article/view/32470},
DOI={10.1609/aaai.v39i4.32470}, number={4},
journal={Proceedings of the AAAI Conference on Artificial Intelligence},
author={Larchenko, Maria and Lobashev, Alexander and Guskov, Dmitry and Palyulin, Vladimir Vladimirovich}, year={2025}, month={Apr.}, pages={4464-4472} }