SpotlessSplats: Ignoring Distractors in 3D Gaussian Splatting
<|reference_start|>SpotlessSplats: Ignoring Distractors in 3D Gaussian Splatting: 3D Gaussian Splatting (3DGS) is a promising technique for 3D reconstruction, offering efficient training and rendering speeds, making it suitable for real-time applications.However, current methods require highly controlled environments (no moving people or wind-blown elements, and consistent lighting) to meet the inter-view consistency assumption of 3DGS. This makes reconstruction of real-world captures problematic. We present SpotLessSplats, an approach that leverages pre-trained and general-purpose features coupled with robust optimization to effectively ignore transient distractors. Our method achieves state-of-the-art reconstruction quality both visually and quantitatively, on casual captures. Additional results available at: https://spotlesssplats.github.io<|reference_end|>
@article{sabour2024spotlesssplats:,
    title={SpotlessSplats: Ignoring Distractors in 3D Gaussian Splatting},
    author={Sara Sabour, Lily Goli, George Kopanas, Mark Matthews, Dmitry Lagun,
  Leonidas Guibas, Alec Jacobson, David J. Fleet, Andrea Tagliasacchi},
    journal={arXiv preprint arXiv:2406.20055},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.20055},
    primaryClass={cs.CV cs.LG}
}