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Identifying Unnecessary 3D Gaussians using Clustering for Fast Rendering of 3D Gaussian Splatting
Feb. 22, 2024, 5:46 a.m. | Joongho Jo, Hyeongwon Kim, Jongsun Park
cs.CV updates on arXiv.org arxiv.org
Abstract: 3D Gaussian splatting (3D-GS) is a new rendering approach that outperforms the neural radiance field (NeRF) in terms of both speed and image quality. 3D-GS represents 3D scenes by utilizing millions of 3D Gaussians and projects these Gaussians onto the 2D image plane for rendering. However, during the rendering process, a substantial number of unnecessary 3D Gaussians exist for the current view direction, resulting in significant computation costs associated with their identification. In this paper, …
2d image 3d scenes abstract arxiv clustering cs.ar cs.cv image nerf neural radiance field projects quality rendering speed terms type
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