Update model card with metadata, links and sample usage
#1
by nielsr HF Staff - opened
README.md
CHANGED
|
@@ -1,14 +1,54 @@
|
|
| 1 |
---
|
| 2 |
-
license: apache-2.0
|
| 3 |
datasets:
|
| 4 |
- jayinnn/Skyfall-GS-datasets
|
|
|
|
|
|
|
| 5 |
---
|
| 6 |
|
| 7 |
-
#
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 8 |
|
| 9 |
-
|
| 10 |
|
| 11 |
-
|
| 12 |
|
| 13 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 14 |
|
|
|
|
|
|
|
|
|
| 1 |
---
|
|
|
|
| 2 |
datasets:
|
| 3 |
- jayinnn/Skyfall-GS-datasets
|
| 4 |
+
license: apache-2.0
|
| 5 |
+
pipeline_tag: image-to-3d
|
| 6 |
---
|
| 7 |
|
| 8 |
+
# Skyfall-GS: Synthesizing Immersive 3D Urban Scenes from Satellite Imagery
|
| 9 |
+
|
| 10 |
+
This repository contains the fused 3D Gaussian Splatting (3DGS) `.ply` files for **Skyfall-GS**, a framework for synthesizing large-scale, immersive 3D urban scenes.
|
| 11 |
+
|
| 12 |
+
[**Project Page**](https://skyfall-gs.jayinnn.dev/) | [**Paper**](https://huggingface.co/papers/2510.15869) | [**GitHub**](https://github.com/jayin92/skyfall-gs)
|
| 13 |
+
|
| 14 |
+
## Description
|
| 15 |
+
|
| 16 |
+
Skyfall-GS is a hybrid framework that synthesizes city-block scale 3D urban scenes by combining satellite reconstruction with diffusion refinement. It leverages readily available satellite imagery to provide realistic coarse geometry and uses open-domain diffusion models to synthesize high-quality close-up appearances. This approach eliminates the need for costly 3D annotations and allows for real-time, immersive 3D exploration.
|
| 17 |
+
|
| 18 |
+
## Visualization
|
| 19 |
+
|
| 20 |
+
The `.ply` files in this repository are intended for use with Gaussian Splatting viewers. For the best experience, use a fused PLY file with the following tools:
|
| 21 |
+
|
| 22 |
+
1. **Mip-Splatting Viewer**: Use the [online viewer](https://niujinshuchong.github.io/mip-splatting-demo). Recommended settings:
|
| 23 |
+
- **Up vector:** `0,0,1`
|
| 24 |
+
- **SH degree:** `1`
|
| 25 |
+
- **Camera origin:** `0,0,200`
|
| 26 |
+
2. **SuperSplat**: You can also use the web-based [SuperSplat Editor](https://superspl.at/editor).
|
| 27 |
+
|
| 28 |
+
## Sample Usage
|
| 29 |
+
|
| 30 |
+
To render a video from a `.ply` file using the scripts provided in the [official repository](https://github.com/jayin92/skyfall-gs):
|
| 31 |
+
|
| 32 |
+
```bash
|
| 33 |
+
python render_video_from_ply.py \
|
| 34 |
+
--ply_path <path_to_ply_file> \
|
| 35 |
+
--camera_path <path_to_camera.json>
|
| 36 |
+
```
|
| 37 |
|
| 38 |
+
## Citation
|
| 39 |
|
| 40 |
+
If you find this work useful, please consider citing:
|
| 41 |
|
| 42 |
+
```bibtex
|
| 43 |
+
@article{lee2025SkyfallGS,
|
| 44 |
+
title = {{Skyfall-GS}: Synthesizing Immersive {3D} Urban Scenes from Satellite Imagery},
|
| 45 |
+
author = {Jie-Ying Lee and Yi-Ruei Liu and Shr-Ruei Tsai and Wei-Cheng Chang and Chung-Ho Wu and Jiewen Chan and Zhenjun Zhao and Chieh Hubert Lin and Yu-Lun Liu},
|
| 46 |
+
journal = {arXiv preprint},
|
| 47 |
+
year = {2025},
|
| 48 |
+
eprint = {2510.15869},
|
| 49 |
+
archivePrefix = {arXiv}
|
| 50 |
+
}
|
| 51 |
+
```
|
| 52 |
|
| 53 |
+
## Acknowledgement
|
| 54 |
+
This codebase is built upon several open-source projects: [Mip-Splatting](https://github.com/autonomousvision/mip-splatting), [WildGuassians](https://github.com/jkulhanek/wild-gaussians), [FlowEdit](https://github.com/fallenshock/FlowEdit), [MoGe](https://github.com/microsoft/MoGe), and [SatelliteSfM](https://github.com/Kai-46/SatelliteSfM).
|