EarthGen: Generating the World from Top-Down Views
<|reference_start|>EarthGen: Generating the World from Top-Down Views: In this work, we present a novel method for extensive multi-scale generative terrain modeling. At the core of our model is a cascade of superresolution diffusion models that can be combined to produce consistent images across multiple resolutions. Pairing this concept with a tiled generation method yields a scalable system that can generate thousands of square kilometers of realistic Earth surfaces at high resolution. We evaluate our method on a dataset collected from Bing Maps and show that it outperforms super-resolution baselines on the extreme super-resolution task of 1024x zoom. We also demonstrate its ability to create diverse and coherent scenes via an interactive gigapixel-scale generated map. Finally, we demonstrate how our system can be extended to enable novel content creation applications including controllable world generation and 3D scene generation.<|reference_end|>
@article{sharma2024earthgen:,
    title={EarthGen: Generating the World from Top-Down Views},
    author={Ansh Sharma, Albert Xiao, Praneet Rathi, Rohit Kundu, Albert Zhai,
  Yuan Shen, Shenlong Wang},
    journal={arXiv preprint arXiv:2409.01491},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.01491},
    primaryClass={cs.CV cs.AI}
}