Terrain Generation

Terrain generation focuses on computationally creating realistic and diverse landscapes, primarily for applications in robotics, gaming, and virtual environments. Current research emphasizes methods leveraging neural networks, such as GANs and diffusion models, alongside procedural techniques like cellular automata and noise functions, often incorporating user-guided control and style transfer for enhanced realism and customization. These advancements improve the fidelity and controllability of generated terrains, impacting fields requiring realistic simulations of complex environments for training robots or creating immersive virtual worlds.