Datasets:
| license: apache-2.0 | |
| task_categories: | |
| - image-to-3d | |
| # The evaluation videos for Skyfall-GS | |
| This repository contains the evaluation videos for the paper [Skyfall-GS: Synthesizing Immersive 3D Urban Scenes from Satellite Imagery](https://arxiv.org/abs/2510.15869). | |
| [**Project Page**](https://skyfall-gs.jayinnn.dev/) | [**GitHub**](https://github.com/jayin92/skyfall-gs) | [**arXiv**](https://arxiv.org/abs/2510.15869) | |
| Skyfall-GS is a hybrid framework that synthesizes immersive city-block scale 3D urban scenes by combining satellite reconstruction with diffusion refinement, eliminating the need for costly 3D annotations. It features real-time, immersive 3D exploration and a curriculum-driven iterative refinement strategy to enhance geometric completeness and photorealistic textures. | |
| ## Citation | |
| If you find this work useful, please consider citing: | |
| ```bibtex | |
| @article{lee2025SkyfallGS, | |
| title = {{Skyfall-GS}: Synthesizing Immersive {3D} Urban Scenes from Satellite Imagery}, | |
| 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}, | |
| journal = {arXiv preprint}, | |
| year = {2025}, | |
| eprint = {2510.15869}, | |
| archivePrefix = {arXiv} | |
| } | |
| ``` |