Implicit Neural Network

Implicit neural networks (INNs) represent data as continuous functions implicitly defined by neural networks, aiming to achieve efficient data encoding and manipulation. Current research focuses on developing INN architectures for various tasks, including video compression and retrieval, image processing (e.g., inpainting, super-resolution), and 3D reconstruction, often employing techniques like hypernetworks and fixed-point iterations. The ability of INNs to handle high-dimensional data efficiently and their potential for improved generalization and robustness makes them a significant area of research with implications across diverse scientific fields and practical applications.