Implicit 3D

Implicit 3D modeling focuses on representing three-dimensional objects and scenes using neural networks, avoiding explicit geometric representations like meshes or point clouds. Current research emphasizes improving the quality and realism of these implicit models, particularly through advancements in neural radiance fields (NeRFs) and related architectures, often incorporating techniques like visual prompts and differentiable rendering for enhanced control and fidelity. This approach is significant for applications ranging from robotic manipulation and augmented reality to high-fidelity 3D reconstruction from various data sources, including images and electron microscopy scans, enabling more efficient and flexible 3D content creation and analysis.