3D Alignment

3D alignment focuses on accurately matching and merging three-dimensional data from various sources, aiming for precise spatial correspondence and efficient integration. Current research emphasizes developing robust and efficient algorithms, often leveraging feature-based approaches and neural radiance fields (NeRFs), to handle large-scale datasets and complex geometries, including applications in machine unlearning and medical imaging. These advancements are significantly impacting fields like cryo-electron microscopy, robotic surgery, and 3D scene reconstruction by enabling more accurate analysis, improved visualization, and enhanced automation.