Mini-Splatting: Representing Scenes with a Constrained Number of Gaussians

arXiv:2403.14166v1 Announce Type: new
Abstract: In this study, we explore the challenge of efficiently representing scenes with a constrained number of Gaussians. Our analysis shifts from traditional graphics and 2D computer vision to the perspective of point clouds, highlighting the inefficient spatial distribution of Gaussian representation as a key limitation in model performance. To address this, we introduce strategies for densification including blur split and depth reinitialization, and simplification through Gaussian binarization and sampling. These techniques reorganize the spatial positions …

abstract analysis arxiv challenge computer computer vision cs.cv distribution explore graphics highlighting key perspective representation spatial study type vision