3D Scene Representation

3D scene representation studies how to encode the shape, appearance, meaning, and motion of environments so they can be reconstructed, rendered, edited, or used by robots and other AI systems. Common approaches include explicit representations such as meshes, voxels, point clouds, Gaussian splats, and scene graphs, alongside implicit neural fields and compact learned tokens; these are used in tasks from novel-view synthesis to dynamic mapping and scene generation. Current work increasingly combines geometric structure with language or semantic features, and tests representations on reconstruction benchmarks as well as navigation, spatial reasoning, and manipulation tasks. A central tension is balancing visual fidelity and geometric reliability against memory, computation, and scalability, especially for large, changing scenes and incomplete observations.