articleJun 16, 2024Closed access

COLMAP-Free 3D Gaussian Splatting

Berkeley College · University of California, Berkeley

Indexed incrossref

Abstract

While neural rendering has led to impressive advances in scene reconstruction and novel view synthesis, it relies heavily on accurately pre-computed camera poses. To relax this constraint, multiple efforts have been made to train Neural Radiance Fields (NeRFs) without pre-processed camera poses. However, the implicit representations of NeRFs provide extra challenges to optimize the 3D structure and camera poses at the same time. On the other hand, the recently proposed 3D Gaussian Splatting provides new opportunities given its explicit point cloud representations. This paper leverages both the explicit geometric representation and the continuity of the input video stream to perform novel view synthesis without…

Citation impact

109
total citations
FWCI
34.04
Percentile
100%
References
0
Citations per year

Authors

6

Topics & keywords

Keywords
  • Computer science
  • Gaussian
  • Computer graphics (images)
  • Physics
No related works found for this paper.