Official Pytorch implementation of "Style Your Hair: Latent Optimization for Pose-Invariant Hairstyle Transfer via Local-Style-Aware Hair Alignment (ECCV 2022)"
Style Your Hair: Latent Optimization for Pose-Invariant Hairstyle Transfer via Local-Style-Aware Hair Alignment
Taewoo Kim*, Chaeyeon Chung*, Yoonseo Kim*, Sunghyun Park, Kangyeol Kim, and Jaegul Choo
*indicates equal contributions.
Abstract Editing hairstyle is unique and challenging due to the complexity and delicacy of hairstyle. Although recent approaches significantly improved the hair details, this is achieved under the assumption that a target hair and a source image are aligned. HairFIT, a pose-invariant hairstyle transfer model, alleviates this assumption, yet it still shows unsatisfactory quality in preserving delicate hair textures. To solve these limitations, we propose a high-performing pose-invariant hairstyle transfer model equipped with a latent optimization and a newly presented local-style-matching loss. In the StyleGAN2 latent space, we first explore a pose-aligned latent code of a target hair with the detailed textures preserved based on local-style-matching. Then, our model inpaints the occlusions of the source considering the aligned target hair and blends both images to produce a final output. The experimental results demonstrate that our model has strengths in transferring a hairstyle under higher pose differences and preserving local hairstyle textures.
Official Implementation of Style Your Hair. KEEP UPDATING! Please Git Pull the latest version.
- Clone the repository:
git clone https://github.com/Taeu/Style-Your-Hair.git
cd Style-Your-Hair
- Install dependencies:
conda create -n {env_name} python=3.7.9
conda activate {env_name}
conda install pytorch==1.8.0 torchvision==0.9.0 torchaudio==0.8.0 cudatoolkit=11.1 -c pytorch -c conda-forge
pip install face_alignment face-recognition gdown ipython matplotlib
Please download the example images.
And put the images in ./ffhq_image/ folder.
Produce the results:
python main.py --input_dir ./ffhq_image/ --im_path1 source.png --im_path2 target.png \
--output_dir ./style_your_hair_output/ \
--warp_loss_with_prev_list delta_w style_hair_slic_large \
--save_all --version final --flip_check
This code borrows heavily from Barbershop.
@article{kim2022style,
title={Style Your Hair: Latent Optimization for Pose-Invariant Hairstyle Transfer via Local-Style-Aware Hair Alignment},
author={Kim, Taewoo and Chung, Chaeyeon and Kim, Yoonseo and Park, Sunghyun and Kim, Kangyeol and Choo, Jaegul},
journal={arXiv preprint arXiv:2208.07765},
year={2022}
}
Licensed under the CC BY-NC-SA 4.0 license (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).