Does Gaussian Splatting need SFM Initialization?

Yalda Foroutan, Daniel Rebain, Kwang Moo Yi, Andrea Tagliasacchi

Does Gaussian Splatting need SFM Initialization?: 9 upvotes on Hugging Face Daily Papers, #6 of 7 papers on 2024-04-22. Day-by-day upvote history.

3D Gaussian Splatting has recently been embraced as a versatile and effective method for scene reconstruction and novel view synthesis, owing to its high-quality results and compatibility with hardware rasterization. Despite its advantages, Gaussian Splatting's reliance on high-quality point cloud initialization by Structure-from-Motion (SFM) algorithms is a significant limitation to be overcome. To this end, we investigate various initialization strategies for Gaussian Splatting and delve into how volumetric reconstructions from Neural Radiance Fields (NeRF) can be utilized to bypass the dependency on SFM data. Our findings demonstrate that random initialization can perform much better if carefully designed and that by employing a combination of improved initialization strategies and structure distillation from low-cost NeRF models, it is possible to achieve equivalent results, or at times even superior, to those obtained from SFM initialization.

Paper page on Hugging Face · arXiv

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