Realistic Relighting

Realistic relighting aims to computationally recreate how objects appear under different lighting conditions, enabling novel view synthesis and augmented reality applications. Current research focuses on developing efficient algorithms, often leveraging neural radiance fields (NeRFs), Gaussian splatting, and diffusion models, to accurately capture and render complex light interactions with materials and geometry, including effects like shadows and reflections. These advancements are improving the realism of digital content creation, virtual and augmented reality experiences, and facilitating more sophisticated analysis of image and video data. The ability to accurately relight scenes is crucial for various fields, from computer graphics and visual effects to robotics and 3D modeling.