Abstract
3D Gaussian splatting (GS) has emerged as a transformative technique in radiance fields. Unlike mainstream implicit neural models, 3D GS uses millions of learnable 3D Gaussians for an explicit scene representation. Paired with a differentiable rendering algorithm, this approach achieves real-time rendering and unprecedented editability, making it a potential game-changer for 3D reconstruction and representation. In the present article, we provide the first systematic overview of the recent developments and critical contributions in 3D GS. We begin with a detailed exploration of the underlying principles and the driving forces behind the emergence of 3D GS, laying the groundwork for understanding its…
Citation impact
38
total citations
- FWCI
- 45.70
- Percentile
- 100%
- References
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Authors
2Topics & keywords
Topics
Keywords
- Computer science
- Rendering (computer graphics)
- Geospatial analysis
- Radiance
- Benchmark (surveying)
- Artificial intelligence
- Data science
- Computer graphics (images)
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