Scene Generation

Scene generation focuses on automatically creating realistic and diverse visual scenes, primarily for applications in robotics, gaming, and autonomous driving simulation. Current research emphasizes generating scenes from various inputs, including text descriptions, 2D images (aerial or ground views), sketches, and even LiDAR data, leveraging model architectures like diffusion models, GANs, and transformers, often integrated with large language models for enhanced control and semantic understanding. This field is significant because high-quality, controllable synthetic scenes are crucial for training and evaluating AI systems, particularly in safety-critical domains, and for creating immersive virtual environments.