Plenoxels: Radiance Fields without Neural Networks

Autor:	Yu, Alex, Fridovich-Keil, Sara, Tancik, Matthew, Chen, Qinhong, Recht, Benjamin, Kanazawa, Angjoo
Rok vydání:	2021
Předmět:	Computer Science - Computer Vision and Pattern Recognition Computer Science - Graphics
Druh dokumentu:	Working Paper
Popis:	We introduce Plenoxels (plenoptic voxels), a system for 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. Comment: For video and code, please see https://alexyu.net/plenoxels
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2112.05131 Zobrazit plný text záznamu View this record from Arxiv