Characterization and Analysis of the 3D Gaussian Splatting Rendering Pipeline
Novel view synthesis, a task generating a 2D image frame from a specific viewpoint within a 3D object or scene, plays a crucial role in 3D rendering. Neural Radiance Field (NeRF) emerged as a prominent method for implementing novel view synthesis, but 3D Gaussian Splatting (3DGS) recently began to emerge as a viable alternative. Despite the tremendous interest from both academia and industry, there has been a lack of research to identify the computational bottlenecks of 3DGS, which is critical for its deployment in real-world products. In this work, we present a comprehensive end-to-end characterization of the 3DGS rendering pipeline, identifying the alpha blending stage within the tile-based rasterizer as causing a significant performance bottleneck. Based on our findings, we discuss several future research directions aiming to inspire continued exploration within this burgeoning application domain.
Authors
- Youngeun Kwon (ORCID: https://orcid.org/0000-0002-4020-8995)
- Yunjae Lee (ORCID: https://orcid.org/0000-0002-1500-3074)
- Minsoo Rhu (ORCID: https://orcid.org/0000-0003-3303-8681)
- Jiwon Lee (ORCID: https://orcid.org/0009-0009-6529-5333)
Institutions
- Korea Advanced Institute of Science and Technology (KR)
Publication Details
- Journal
- IEEE Computer Architecture Letters
- Published
- 2024-11-21
- DOI
- https://doi.org/10.1109/lca.2024.3504579
- Citations
- 1
- Primary Topic
- Computer Graphics and Visualization Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.63