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pro vyhledávání: '"Goli, Lily"'
Autor:
Sabour, Sara, Goli, Lily, Kopanas, George, Matthews, Mark, Lagun, Dmitry, Guibas, Leonidas, Jacobson, Alec, Fleet, David J., Tagliasacchi, Andrea
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 pe
Externí odkaz:
http://arxiv.org/abs/2406.20055
Autor:
Shabanov, Ahan, Govindarajan, Shrisudhan, Reading, Cody, Goli, Lily, Rebain, Daniel, Yi, Kwang Moo, Tagliasacchi, Andrea
Publikováno v:
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024, pp. 20571-20580
Largely due to their implicit nature, neural fields lack a direct mechanism for filtering, as Fourier analysis from discrete signal processing is not directly applicable to these representations. Effective filtering of neural fields is critical to en
Externí odkaz:
http://arxiv.org/abs/2404.13024
Neural Radiance Fields (NeRFs) have shown promise in applications like view synthesis and depth estimation, but learning from multiview images faces inherent uncertainties. Current methods to quantify them are either heuristic or computationally dema
Externí odkaz:
http://arxiv.org/abs/2309.03185
We introduce a technique for pairwise registration of neural fields that extends classical optimization-based local registration (i.e. ICP) to operate on Neural Radiance Fields (NeRF) -- neural 3D scene representations trained from collections of cal
Externí odkaz:
http://arxiv.org/abs/2211.01600