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| title: RFMSR Super-Resolution | |
| emoji: 🔍 | |
| colorFrom: red | |
| colorTo: gray | |
| sdk: gradio | |
| sdk_version: 6.22.0 | |
| app_file: app.py | |
| short_description: Residual Flow Matching for 4x image super-resolution | |
| python_version: "3.12" | |
| startup_duration_timeout: 30m | |
| # RFMSR: Residual Flow Matching for Image Super-Resolution | |
| This Space demos [RFMSR](https://huggingface.co/papers/2607.12753), a flow-matching-based image super-resolution model. | |
| Upload a low-quality image and get a 4× upscaled result. The model performs residual flow matching in the latent space of the SD2.1 VAE, guided by DINOv2 semantic features. | |
| ## Usage | |
| 1. Upload a low-quality image (or click an example) | |
| 2. Adjust the upscale factor and number of steps if desired | |
| 3. Click "Super-Resolve" | |
| **Multi-step mode** (default, 15 steps) produces sharp, high-quality results. **One-step mode** (1 step) is faster but produces softer/blurrier output. | |
| ## Links | |
| - [Paper (arXiv 2607.12753)](https://arxiv.org/abs/2607.12753) | |
| - [GitHub](https://github.com/Faze-Hsw/RFMSR) | |
| - [Hugging Face Model](https://huggingface.co/frozen2001/RFMSR) |