BOGausS: Better Optimized Gaussian Splatting
원문 초록
3D Gaussian Splatting (3DGS) proposes an efficient solution for novel view synthesis. Its framework provides fast and high-fidelity rendering. Although less complex than other solutions such as Neural Radiance Fields (NeRF), there are still some challenges building smaller models without sacrificing quality. In this study, we perform a careful analysis of 3DGS training process and propose a new optimization methodology. Our Better Optimized Gaussian Splatting (BOGausS) solution is able to generate models up to ten times lighter than the original 3DGS with no quality degradation, thus significantly boosting the performance of Gaussian Splatting compared to the state of the art.
함께 살펴볼 논문
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R3eVision: A Survey on Robust Rendering, Restoration, and Enhancement for 3D Low-Level Vision
Speedy Deformable 3D Gaussian Splatting: Fast Rendering and Compression of Dynamic Scenes
CasualHDRSplat: Robust High Dynamic Range 3D Gaussian Splatting from Casually Captured Videos
Visibility-Uncertainty-guided 3D Gaussian Inpainting via Scene Conceptional Learning
SVG-IR: Spatially-Varying Gaussian Splatting for Inverse Rendering
Luminance-GS: Adapting 3D Gaussian Splatting to Challenging Lighting Conditions with View-Adaptive Curve Adjustment
토론
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