Coordinate Network

Coordinate networks are neural network architectures that represent signals as continuous functions of spatial coordinates, offering efficient and compact representations for various data types. Current research focuses on improving their performance by addressing spectral bias through normalization techniques, integrating them with other architectures like multi-plane representations for enhanced detail capture, and exploring alternative activation functions and positional encodings for improved efficiency and high-frequency information preservation. These advancements are significantly impacting fields like image processing, medical imaging, and 3D scene representation by enabling faster training, higher compression ratios, and improved reconstruction quality in applications ranging from novel view synthesis to solving partial differential equations.