File size: 1,437 Bytes
de739f3 10c5536 de739f3 008f2b8 de739f3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 | ---
license: cc-by-nc-nd-4.0
pipeline_tag: image-to-3d
tags:
- 3D
- Avatar
---
# UP2You: Fast Reconstruction of Yourself from Unconstrained Photo Collections
UP2You is a tuning-free framework for 3D human reconstruction from unconstrained photo collections.
* **Paper**: [UP2You: Fast Reconstruction of Yourself from Unconstrained Photo Collections](https://arxiv.org/abs/2509.24817)
* **Project Page**: [https://zcai0612.github.io/UP2You/](https://zcai0612.github.io/UP2You/)
* **Code**: [https://github.com/zcai0612/UP2You](https://github.com/zcai0612/UP2You)
## Sample Usage
To run the inference pipeline with example images:
```bash
python inference_low_gpu.py \
--base_model_path stabilityai/stable-diffusion-2-1-base \
--segment_model_name briaai/RMBG-2.0 \
--data_dir examples \
--output_dir outputs \
```
Alternatively, you can use the provided shell script:
```bash
bash run.sh
```
`examples` is the folder containing your unconstrained photos, and `outputs` is the directory where the generated 3D reconstruction results will be saved.
## Citation
If you find our work useful, please cite:
```bibtex
@article{cai2025up2you,
title={UP2You: Fast Reconstruction of Yourself from Unconstrained Photo Collections},
author={Cai, Zeyu and Li, Ziyang and Li, Xiaoben and Li, Boqian and Wang, Zeyu and Zhang, Zhenyu and Xiu, Yuliang},
journal={arXiv preprint arXiv:2509.24817},
year={2025}
}
``` |