Photorealistic Rendering

Photorealistic rendering aims to generate highly realistic images of 3D scenes, focusing on accurately simulating light interactions and material properties. Current research emphasizes efficient sampling techniques, such as importance sampling with neural networks and Gaussian splatting, to improve rendering speed and quality, particularly for dynamic scenes and complex geometries like human avatars and urban environments. These advancements are driving progress in applications ranging from virtual and augmented reality to autonomous navigation and 3D modeling, enabling more immersive and interactive experiences.