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Running on Zero
| title: SIFT-VTON | |
| emoji: 👕 | |
| colorFrom: indigo | |
| colorTo: pink | |
| sdk: gradio | |
| sdk_version: 6.24.0 | |
| app_file: app.py | |
| short_description: Virtual try-on with SIFT correspondence supervision | |
| python_version: "3.10" | |
| startup_duration_timeout: 1h | |
| license: cc-by-nc-sa-4.0 | |
| # SIFT-VTON | |
| Interactive demo of **SIFT-VTON: Geometric Correspondence Supervision on Cross-Attention for | |
| Virtual Try-On** (ICPR 2026). | |
| - Paper: https://huggingface.co/papers/2605.01296 | |
| - Model: https://huggingface.co/takesuke/SIFT-VTON | |
| - Code: https://github.com/takesukeDS/SIFT-VTON | |
| The sampling path mirrors the authors' `inference_hf.py` (PLMS, 50 steps, cfg 1.5, | |
| `--start_from_noised_agn`, `--repaint`) at the training resolution of 512×384. Because the model | |
| consumes VITON-HD-style inputs (agnostic person image + agnostic mask + DensePose), the Space runs | |
| that preprocessing chain on the fly — SCHP human parsing, OpenPose body keypoints and | |
| DensePose (`densepose_rcnn_R_50_FPN_s1x`) — so arbitrary photographs can be used. | |
| ## Credits | |
| The preprocessing code (vendored `detectron2` / `densepose`, human parsing, OpenPose, the VITON-HD | |
| agnostic-mask builder) and the preprocessing checkpoints come from | |
| [IDM-VTON](https://huggingface.co/spaces/yisol/IDM-VTON) (CC BY-NC-SA 4.0). The example person and | |
| garment images are VITON-HD test-set items redistributed from the same Space under CC BY-NC-SA 4.0. | |
| The SIFT-VTON weights are licensed CC BY-NC-SA 4.0 — this demo is for non-commercial research use. | |