The official repository of the papers:
- "TryOffDiff: Virtual-Try-Off via High-Fidelity Garment Reconstruction using Diffusion Models",
- "MGT: Extending Virtual Try-Off to Multi-Garment Scenarios"
- [2025-09-01]: Demo is accepted at ICCV'25 Demo Track, will be presented on Oct 21st, 2025.
- [2025-07-25]: Paper1 accepted at BMVC'25, will be presented on Nov 24-27, 2025 (tbd).
- [2025-07-11]: Paper2 accepted at ICCV'25 Workshop, will be presented on Oct 20th, 2025.
- [2025-07-10]: Code for new features made available.
- [2025-04-17]: Paper2 (follow-up work) appeared on arXiv with improvements, e.g. multi-garment try-off.
- [2025-03-26]: Demo is accepted at CVPR'25 Demo Track, presented on June 13, 2025.
- [2024-12-03]: Training, Inference, and Evaluation scripts made available.
- [2024-11-27]: Paper1 appeared on arXiv.
Please refer to the instructions.
The following project/directory structure is adopted: Cookiecutter Data Science-v2 by DrivenData
βββ notebooks/ <- Jupyter notebooks
βββ references/ <- Manuals and all other explanatory materials.
βββ LICENSE
βββ README.md
βββ pyproject.toml <- Project configuration file with package metadata
|
βββ tryoffdiff/ <- Source code for use in this project.
βββ modeling/
β βββ __init__.py
β βββ eval.py <- Code to evaluate models
β βββ model.py <- Model implementations
β βββ predict.py <- Code to run model inference with trained models
β βββ train.py <- Code to train models
|
βββ __init__.py <- Makes `tryoffdiff` a Python module
βββ config.py <- Store configuration variables for training and inference
βββ dataset.py <- Download and clean datasets VITON-HD & Dress Code
βββ features.py <- Code to create features for modeling
βββ plots.py <- Code to create visualizations
Our code relies on PyTorch, with π€ Diffusers for diffusion model components
and π€ Accelerate for multi-GPU training.
We adopt Stable Diffusion-v1.4 as the base model and use
SigLIP as the image encoder.
For evaluation, we use IQA_PyTorch,
clean-fid,
and DISTS-pytorch.
TL;DR: Not available for commercial use, unless the FULL source code is open-sourced!
This project is intended solely for academic research. No commercial benefits are derived from it.
The code, datasets, and models are published under the Server Side Public License (SSPL).
If you find this repository useful in your research, please consider giving a star β and a citation:
@inproceedings{velioglu2025tryoffdiff,
title = {TryOffDiff: Virtual-Try-Off via High-Fidelity Garment Reconstruction using Diffusion Models},
author = {Velioglu, Riza and Bevandic, Petra and Chan, Robin and Hammer, Barbara},
booktitle = {BMVC},
year = {2025},
note = {\url{https://doi.org/nt3n}}
}
@inproceedings{velioglu2025mgt,
title = {MGT: Extending Virtual Try-Off to Multi-Garment Scenarios},
author = {Velioglu, Riza and Bevandic, Petra and Chan, Robin and Hammer, Barbara},
booktitle = {ICCVW},
year = {2025},
note = {\url{https://doi.org/pn67}}
}
