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arXiv Computer Vision By Vitor Matias, Filipe Nascimento, Kiyohiro Nakayama, Jo\~ao Paulo Lima, M\'arcus Lobo, Gordon Wetzstein, Leonidas Guibas, Afonso Paiva, Tiago Novello

PCAsplat: Gaussian Splatting with Local PCA Regularization

Read the original on arXiv Computer Vision →

PCAsplat introduces a geometry‑aware regularization framework for Gaussian splatting that uses differentiable local PCA to update Gaussians even when they are occluded or contribute little to sampled camera rays. By regularizing PCA eigenvalues and aligning Gaussian normals with neighborhood normals, the method encourages Gaussians to move onto the underlying surface with isotropic tangent‑plane coverage, thereby reducing floaters. Experiments on DTU, Tanks and Temples, and NeRF Synthetic demonstrate that PCAsplat produces surface‑aligned splats that improve geometry‑processing tasks such as point cloud segmentation and Poisson reconstruction while remaining competitive in novel view synthesis and mesh extraction.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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