Neural Reflectance

Neural reflectance focuses on using neural networks to model and manipulate the way light interacts with surfaces, aiming to accurately represent and reconstruct 3D scenes from images. Current research emphasizes developing efficient neural network architectures, such as NeRFs and variations incorporating BRDF models, to achieve realistic rendering and material editing from limited input data, including single-view or multi-view images under varying lighting conditions. This field is significant for advancing computer vision, computer graphics, and remote sensing applications, enabling tasks like novel view synthesis, 3D reconstruction, and true color correction in challenging environments like underwater imaging. The ability to accurately model complex reflectance properties improves the realism and fidelity of digital representations of the real world.