3D Gaussian Splatting for Real-Time Radiance Field Rendering
Institut national de recherche en sciences et technologies du numérique · Université Côte d'Azur · +2 more institutions
Abstract
Radiance Field methods have recently revolutionized novel-view synthesis of scenes captured with multiple photos or videos. However, achieving high visual quality still requires neural networks that are costly to train and render, while recent faster methods inevitably trade off speed for quality. For unbounded and complete scenes (rather than isolated objects) and 1080p resolution rendering, no current method can achieve real-time display rates. We introduce three key elements that allow us to achieve state-of-the-art visual quality while maintaining competitive training times and importantly allow high-quality real-time (≥ 30 fps) novel-view synthesis at 1080p resolution. First, starting from sparse points…
Citation impact
- FWCI
- 486.68
- Percentile
- 100%
- References
- 45
Authors
4- BKBernhard KerblCorresponding
Institut national de recherche en sciences et technologies du numérique, Université Côte d'Azur
- GKGeorgios Kopanas
Institut national de recherche en sciences et technologies du numérique, Université Côte d'Azur, Fondation Sophia Antipolis
- TLThomas Leimkühler
Max Planck Institute for Informatics
- GDGeorge Drettakis
Institut national de recherche en sciences et technologies du numérique
Topics & keywords
- Computer science
- Rendering (computer graphics)
- Radiance
- Artificial intelligence
- Computer vision
- Computer graphics (images)
- View synthesis
- Light field