Plenoxels: Radiance Fields without Neural Networks
Sara Fridovich-Keil, Alex Yu, Matthew Tancik, Qinhong Chen, Benjamin Recht, Angjoo Kanazawa
Abstract
We introduce Plenoxels (plenoptic voxels), a systemfor photorealistic view synthesis. Plenoxels represent a scene as a sparse 3D grid with spherical harmonics. This representation can be optimized from calibrated images via gradient methods and regularization without any neural components. On standard, benchmark tasks, Plenoxels are optimized two orders of magnitude faster than Neural Radiance Fields with no loss in visual quality. For video and code, please see https://alexyu.net/plenoxels.
Topics & Concepts
RadianceComputer scienceVoxelArtificial neural networkSpherical harmonicsArtificial intelligenceGridBenchmark (surveying)Code (set theory)Representation (politics)Computer visionRegularization (linguistics)VisualizationMathematicsOpticsPhysicsLawMathematical analysisProgramming languageGeographyPoliticsPolitical scienceGeodesySet (abstract data type)GeometryAdvanced Vision and ImagingComputer Graphics and Visualization Techniques3D Shape Modeling and Analysis