Illumination Model

Illumination modeling aims to realistically represent and manipulate light in scenes, crucial for tasks like image synthesis, 3D reconstruction, and robotic vision. Current research focuses on developing efficient and accurate models, often employing neural networks (e.g., radiance fields, voxel-based representations) to capture complex lighting interactions, including direct and indirect illumination, and integrating physical principles for improved realism. These advancements enable applications such as high-quality image generation with controllable lighting, improved 3D scene reconstruction from limited data, and enhanced robotic perception in challenging lighting conditions.