--- license: mit language: - en tags: - pytorch - virtual-try-on - viton - image-to-image - fashion pipeline_tag: image-to-image datasets: - NguyenDinhHieu/VITON-Extends-DB --- # VITON-Extends — Model weights & inference bundle **Enhancing Pose Adaptability in Virtual Try-On Systems** | Author | Affiliation | ORCID | |--------|-------------|--------| | **Nguyen Dinh Hieu** | FPT University, Hanoi, Vietnam | [0009-0002-6683-8036](https://orcid.org/0009-0002-6683-8036) | | **Tran Minh Khuong** | FPT University, Hanoi, Vietnam | — | | **Phan Duy Hung** | FPT University, Hanoi, Vietnam | [0000-0002-6033-6484](https://orcid.org/0000-0002-6033-6484) | **Contact:** [hieundhe180318@fpt.edu.vn](mailto:hieundhe180318@fpt.edu.vn), [khuongtmhe180089@fpt.edu.vn](mailto:khuongtmhe180089@fpt.edu.vn), [hungpd2@fe.edu.vn](mailto:hungpd2@fe.edu.vn) --- ## What is in this Hub repository? This **model** repo ships two top-level folders: | Folder on Hub | Role | |----------------|------| | **`VITON-Extends_test/`** | Code and assets to run **inference / demo** (`test.py`, networks, options, etc.). | | **`VITON-Extends-Train/`** | **Training-side** bundle (scripts, configs, or checkpoints—whatever you packaged locally under that directory). | Download the full repo (or a subset with `allow_patterns`) and point your local paths to these folders as in the [GitHub README](https://github.com/nguyendinhhieu1309/VITON-Extends). **Dataset (images)** is hosted separately: **[NguyenDinhHieu/VITON-Extends-DB](https://huggingface.co/datasets/NguyenDinhHieu/VITON-Extends-DB)** (see that dataset card for `Train.zip` / `Test.zip` and extraction). --- ## Abstract Garment fitting in virtual try-on often fails under **complex poses**, **occlusions**, and **misalignment** between person and garment. VITON-Extends improves **pose adaptability** and **garment warping** with a **global appearance flow** model, **StyleGAN-style** global modulation, and a **local flow refinement** stage. On the VITON benchmark, results are strong especially in challenging poses. **Paper:** [Springer LNCS (IUKM 2025), DOI 10.1007/978-981-96-4606-7_21](https://doi.org/10.1007/978-981-96-4606-7_21) **Code:** [github.com/nguyendinhhieu1309/VITON-Extends](https://github.com/nguyendinhhieu1309/VITON-Extends) --- ## Quick download (Python) ```python from huggingface_hub import snapshot_download path = snapshot_download( repo_id="NguyenDinhHieu/VITON-Extends", local_dir="./VITON-Extends_hf", ) # Then use ./VITON-Extends_hf/VITON-Extends_test/ and ./VITON-Extends_hf/VITON-Extends-Train/ ``` --- ## Environment (reference) Versions below match the **paper / reference** setup; your local `VITON-Extends_*` trees may ship their own `requirements.txt`—prefer those for exact pins. | Component | Reference version | |-----------|-------------------| | PyTorch | 2.2.1+cu118 (example) | | TorchVision | 0.17.1+cu118 | | CuPy | 13.3.0 | | OpenCV | 4.10.0 | | Python | 3.12 (or as in project env) | --- ## Training & testing (outline) 1. **Data:** Use **[VITON-Extends-DB](https://huggingface.co/datasets/NguyenDinhHieu/VITON-Extends-DB)** — unzip `Train.zip` / `Test.zip`, set `dataroot` to `train/` or `test/` as in the dataset card. 2. **Checkpoints:** Place warping / generation weights where the GitHub repo expects (e.g. under `checkpoints/VITON-Extends/`). 3. **Train:** Run the shell scripts under `scripts/` from the GitHub repository (parser-based then parser-free stages). 4. **Test:** From the downloaded **`VITON-Extends_test/`** tree, follow repo instructions, e.g. `python test.py --name demo --resize_or_crop None --batchSize 1 --gpu_ids 0` For **FID** and extra assets, see links in the [GitHub README](https://github.com/nguyendinhhieu1309/VITON-Extends). --- ## Results (qualitative) ![VITON-Extends results](https://github.com/user-attachments/assets/b9a9b46f-753e-485b-b9ad-156b7b588324) --- ## Citation ```bibtex @inproceedings{hieu2025vitonextends, title = {Enhancing Pose Adaptability in Virtual Try-On Systems}, author = {Hieu, Nguyen Dinh and Khuong, Tran Minh and Hung, Phan Duy}, booktitle = {Integrated Uncertainty in Knowledge Modelling and Decision Making (IUKM 2025)}, series = {Lecture Notes in Computer Science}, volume = {15585}, publisher = {Springer}, address = {Singapore}, year = {2025}, doi = {10.1007/978-981-96-4606-7_21} } ``` --- ## Acknowledgements Built on virtual try-on and flow-based clothed-person generation ideas; base code lineage includes **ClothFlow**. Full credits appear in the [GitHub repository](https://github.com/nguyendinhhieu1309/VITON-Extends).