Procedural Model

Procedural modeling generates complex data, such as images or 3D models, using algorithms and parameters, rather than relying solely on pre-existing data. Current research focuses on improving realism and controllability, often integrating large language models (LLMs) to enable user-friendly text-based generation and manipulation of intricate scenes and objects, and employing neural networks for inverse procedural modeling to reconstruct 3D structures from images. This approach offers significant advantages in creating large, annotated datasets for training machine learning models, accelerating data-intensive tasks in fields like computer vision, 3D modeling, and computer graphics, and reducing the need for expensive and time-consuming data acquisition.