Instructions to use csbowei/ART with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use csbowei/ART with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("csbowei/ART") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
| base_model: black-forest-labs/FLUX.1-Kontext-dev | |
| base_model_relation: adapter | |
| library_name: diffusers | |
| license: apache-2.0 | |
| tags: | |
| - lora | |
| - flux | |
| - flux-kontext | |
| - image-to-image | |
| - makeup-transfer | |
| - makeup-removal | |
| - safetensors | |
| <div align='center'> | |
| <h1 align="center">[ECCV 2026] Anchoring on Reality: Breaking the Pseudo-Target Ceiling in Makeup Transfer</h1> | |
| Bo Wei<sup> 1*</sup>  | |
| <a href='https://scholar.google.com/citations?user=wLTXeNwAAAAJ&hl=en&oi=ao' target='_blank'>Xianhui Lin</a><sup> 2†</sup>  | |
| Yi Dong<sup> 2</sup>  | |
| Zhongzhong Li<sup> 2</sup>  | |
| Zonghui Li<sup> 2</sup>  | |
| <a href='https://scholar.google.com/citations?hl=en&user=BhmLztgAAAAJ' target='_blank'>Zirui Wang</a><sup> 2</sup>  | |
| </div> | |
| <div align='center'> | |
| <a href='https://scholar.google.com/citations?hl=en&user=12MzNVkAAAAJ' target='_blank'>Jiachen Yang</a><sup> 2</sup>  | |
| Xing Liu<sup> 2</sup>  | |
| Hong Gu<sup> 2</sup>  | |
| <a href='https://scholar.google.com/citations?hl=en&user=tmT_voUAAAAJ' target='_blank'>Xiaoming Li</a><sup> 3✉</sup>  | |
| <a href='https://scholar.google.com/citations?hl=en&user=rUOpCEYAAAAJ' target='_blank'>Wangmeng Zuo</a><sup> 1✉</sup> | |
| </div> | |
| <div align='center'> | |
| <sup>1 </sup>Harbin Institute of Technology  | |
| <sup>2 </sup>vivo BlueImage Lab  | |
| <sup>3 </sup>Nanjing University | |
| </div> | |
| <div align='center'> | |
| <small><sup>*</sup> Work done during an internship at vivo.</small>  | |
| <small><sup>†</sup> Project lead</small> | |
| </div> | |
| <div align="center"> | |
| <p> | |
| <a href="https://arxiv.org/abs/2606.31089" target="_blank"><img src="https://img.shields.io/badge/arXiv-ART-red" alt="arXiv link"></a> | |
| <a href="https://csbowei.github.io/ART/" target="_blank"><img src="https://img.shields.io/badge/Project-Homepage-green" alt="project homepage"></a> | |
| <a href="https://github.com/csbowei/ART" target="_blank"><img src="https://img.shields.io/badge/GitHub-Code-blue?logo=github" alt="GitHub code"></a> | |
| <a href="https://drive.google.com/drive/folders/1UfUUAk86fWWzYsZcGOzpTmAWa32IwK21?usp=drive_link" target="_blank"><img src="https://img.shields.io/badge/Dataset-MF2K-purple?logo=googledrive&logoColor=white" alt="MF2K Dataset"></a> | |
| </p> | |
| </div> | |
| This repository provides the model weights for **ART: Anchoring on Reality: Breaking the Pseudo-Target Ceiling in Makeup Transfer**. | |
| ART is a makeup transfer framework that applies a reference cosmetic style to a source face while preserving identity, geometry, and fine-grained makeup details. | |
| ## Files | |
| | File | Task | | |
| | ----------------------------------- | --------------- | | |
| | `art_transfer_lora_512.safetensors` | Makeup transfer | | |
| | `art_transfer_lora_1024.safetensors` | Makeup transfer | | |
| | `art_demakeup_lora_512.safetensors` | Makeup removal | | |
| | `art_demakeup_lora_1024.safetensors` | Makeup removal | | |
| Higher-resolution checkpoints will be released in the future. Stay tuned. | |
| ## Usage | |
| These LoRA adapters are for [`black-forest-labs/FLUX.1-Kontext-dev`](https://huggingface.co/black-forest-labs/FLUX.1-Kontext-dev). | |
| Refer to the project repository: https://github.com/csbowei/ART | |
| Example: | |
| ```bash | |
| # Makeup transfer: apply the reference's makeup onto the input face | |
| python infer.py \ | |
| --task mt \ | |
| --input ./examples/source/src_001.jpg \ | |
| --ref ./examples/ref/ref_001.jpg \ | |
| --lora_path /path/to/art_transfer_lora_1024.safetensors \ | |
| --resolution 1024 | |
| ``` | |
| ```bash | |
| # Makeup removal: strip cosmetics from the input face | |
| python infer.py \ | |
| --task demakeup \ | |
| --input ./examples/ref/ref_002.jpg \ | |
| --lora_path /path/to/art_demakeup_lora_1024.safetensors \ | |
| --resolution 1024 | |
| ``` | |
| ## Citation | |
| ```bibtex | |
| @article{wei2026art, | |
| title={Anchoring on Reality: Breaking the Pseudo-Target Ceiling in Makeup Transfer}, | |
| author={Wei, Bo and Lin, Xianhui and Dong, Yi and Li, Zhongzhong and Li, Zonghui and Wang, Zirui and Yang, Jiachen and Liu, Xing and Gu, Hong and Li, Xiaoming and Zuo, Wangmeng}, | |
| journal={arXiv preprint arXiv:2606.31089}, | |
| year={2026} | |
| } | |
| ``` | |