Volumetric Representation
Volumetric representation in computer vision and graphics aims to create 3D models of scenes and objects by representing them as continuous volumes of data, rather than discrete surfaces or points. Current research focuses on improving the efficiency and accuracy of these representations, often employing neural networks (like NeRFs and their variants) and novel discretization techniques (e.g., using Voronoi tessellations or octrees) to handle complex geometries and reduce computational costs. This work has significant implications for various applications, including 3D reconstruction, view synthesis, object detection, and medical imaging, by enabling more realistic and efficient 3D modeling and manipulation.
Papers
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