April 22, 2024, 4:44 a.m. | Yalda Foroutan, Daniel Rebain, Kwang Moo Yi, Andrea Tagliasacchi

cs.CV updates on arXiv.org arxiv.org

arXiv:2404.12547v1 Announce Type: new
Abstract: 3D Gaussian Splatting has recently been embraced as a versatile and effective method for scene reconstruction and novel view synthesis, owing to its high-quality results and compatibility with hardware rasterization. Despite its advantages, Gaussian Splatting's reliance on high-quality point cloud initialization by Structure-from-Motion (SFM) algorithms is a significant limitation to be overcome. To this end, we investigate various initialization strategies for Gaussian Splatting and delve into how volumetric reconstructions from Neural Radiance Fields (NeRF) can …

abstract advantages algorithms arxiv cloud cs.cv hardware novel quality reliance results synthesis type view

Founding AI Engineer, Agents

@ Occam AI | New York

AI Engineer Intern, Agents

@ Occam AI | US

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Business Intelligence Architect - Specialist

@ Eastman | Hyderabad, IN, 500 008