Neural Implicit Field

Neural implicit fields represent 3D objects and scenes as continuous functions learned by neural networks, aiming to overcome limitations of traditional explicit representations. Current research focuses on improving efficiency and accuracy through architectures like Neural Radiance Fields (NeRF) and their variants, often incorporating techniques such as octrees and multi-grid approaches for faster rendering and editing. These advancements are driving progress in applications like 3D reconstruction, visual localization, and shape manipulation, offering more flexible and efficient methods for handling complex geometries and appearances.