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arxiv: 1707.03383 · v1 · submitted 2017-07-11 · 📊 stat.ML · cs.CV

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A step towards procedural terrain generation with GANs

Christopher Beckham , Christopher Pal
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classification 📊 stat.ML cs.CV
keywords beengenerationproceduralstepterrainadvancesalgorithmsavailable
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Procedural terrain generation for video games has been traditionally been done with smartly designed but handcrafted algorithms that generate heightmaps. We propose a first step toward the learning and synthesis of these using recent advances in deep generative modelling with openly available satellite imagery from NASA.

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  1. InfiniteDiffusion: Bridging Learned Fidelity and Procedural Utility for Open-World Terrain Generation

    cs.CV 2025-12 unverdicted novelty 6.0

    InfiniteDiffusion adapts diffusion models to produce infinite, seed-consistent, high-fidelity terrain with procedural-noise-like access and 9x speed over prior methods.