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license: apache-2.0
tags:
- face
- uv-texture
- latent-diffusion
- 3d-reconstruction
- basel-face-model
---
# UV-IDM: Identity-Conditioned Latent Diffusion Model for Face UV-Texture Generation
Official implementation from [UV-IDM (GitHub)](https://github.com/Luh1124/UV-IDM), presented at CVPR 2024.
## Overview
UV-IDM generates photo-realistic facial UV textures based on the Basel Face Model (BFM). It leverages a latent diffusion model (LDM) for detailed texture generation and an identity-conditioned module to preserve identity consistency during 3D face reconstruction.
## Key Features
- **Identity-Conditioned Generation**: Uses any in-the-wild image as a robust condition to guide texture generation while maintaining identity
- **BFM-Compatible**: Easily adaptable to different BFM-based 3D face reconstruction methods
- **High-Fidelity Output**: Generates detailed facial textures within seconds
- **BFM-UV Dataset**: Large-scale publicly available UV-texture dataset based on BFM
## Checkpoint Structure
Place the downloaded checkpoint files in this directory with the following structure:
```
./
├── checkpoints/ # Model weights
├── pretrained/ # Pre-trained models
├── BFM/ # Basel Face Model files
└── third_party/ # Third-party dependencies
```
Download the checkpoint files from the [official link](https://github.com/Luh1124/UV-IDM) (see README for the Google Drive link).
## Usage
### Inference
Create a filelist containing absolute paths to your input images, then run:
```bash
# Quick start with example images
CUDA_VISIBLE_DEVICES=0 python scripts/visualize.py --images_list_file test.txt --outdir test_imgs/output
# With your own images
CUDA_VISIBLE_DEVICES=0 python scripts/visualize.py --images_list_file your_txt_list --outdir your_output_path
```
The network outputs: render image, UV map, and OBJ file.
## Citation
```bibtex
@inproceedings{li2024uv,
title={UV-IDM: Identity-Conditioned Latent Diffusion Model for Face UV-Texture Generation},
author={Li, Hong and Feng, Yutang and Xue, Song and Liu, Xuhui and Zeng, Bohan and Li, Shanglin and Liu, Boyu and Liu, Jianzhuang and Han, Shumin and Zhang, Baochang},
booktitle={CVPR},
year={2024}
}
```
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