| --- |
| license: apache-2.0 |
| tags: |
| - controlnet |
| - stable-diffusion |
| - satellite-imagery |
| - osm |
| - image-to-image |
| - diffusers |
| base_model: stabilityai/stable-diffusion-2-1-base |
| pipeline_tag: image-to-image |
| library_name: diffusers |
| --- |
| |
| # VectorSynth |
|
|
| **VectorSynth** is a ControlNet model that generates satellite imagery from OpenStreetMap (OSM) vector data embeddings. It conditions [Stable Diffusion 2.1 Base](https://huggingface.co/stabilityai/stable-diffusion-2-1-base) on rendered OSM text to synthesize realistic aerial imagery. |
|
|
| ## Model Description |
|
|
| VectorSynth uses a two-stage pipeline: |
| 1. **RenderEncoder**: Projects 768-dim CLIP text embeddings of OSM text to 3-channel control images |
| 2. **ControlNet**: Conditions Stable Diffusion 2.1 on the rendered control images |
|
|
| This model uses standard CLIP embeddings. For the COSA embedding variant, see [VectorSynth-COSA](https://huggingface.co/MVRL/VectorSynth-COSA). |
|
|
| ## Files |
|
|
| - `config.json` - ControlNet configuration |
| - `diffusion_pytorch_model.safetensors` - ControlNet weights |
| - `render_encoder/clip-render_encoder.pth` - RenderEncoder weights |
| - `render.py` - RenderEncoder class definition |
|
|
| ## Citation |
|
|
| ```bibtex |
| @inproceedings{cher2025vectorsynth, |
| title={VectorSynth: Fine-Grained Satellite Image Synthesis with Structured Semantics}, |
| author={Cher, Daniel and Wei, Brian and Sastry, Srikumar and Jacobs, Nathan}, |
| year={2025}, |
| eprint={arXiv:2511.07744}, |
| note={arXiv preprint} |
| } |
| ``` |
|
|
| ## Related Models |
|
|
| - [VectorSynth-COSA](https://huggingface.co/MVRL/VectorSynth-COSA) - COSA embedding variant |
| - [GeoSynth](https://huggingface.co/MVRL/GeoSynth) - Text-to-satellite image generation |
