---
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
---
[ECCV 2026] Anchoring on Reality: Breaking the Pseudo-Target Ceiling in Makeup Transfer
Bo Wei
1*
Xianhui Lin 2†
Yi Dong
2
Zhongzhong Li
2
Zonghui Li
2
Zirui Wang 2
1 Harbin Institute of Technology
2 vivo BlueImage Lab
3 Nanjing University
* Work done during an internship at vivo.
† Project lead
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}
}
```
