Implicit Neural Field

Implicit neural fields (INFs) represent 3D shapes and scenes using neural networks, offering compact and efficient representations compared to traditional methods. Current research focuses on improving INF applications in diverse areas, including 3D object reconstruction and separation from limited input (e.g., user clicks or sparse views), high-compression of microscopy images, and generating novel INFs via diffusion models. These advancements are significantly impacting fields like computer vision, medical imaging, and remote sensing by enabling high-fidelity 3D modeling from limited data and facilitating efficient data storage and processing.