arXiv Computer Vision By Tze Ho Elden Tse, Jizong Peng, Richard Chen, Angela Yao

AffineGS: Unlocking Accurate Geometry in 3DGS via Spatially Varying Affine Rectification

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The paper introduces AffineGS, a method that improves the geometric accuracy of 3D Gaussian Splatting (3DGS) by applying a spatially varying affine rectification to monocular depth estimates. It identifies that monocular depth networks suffer from region-dependent, piecewise-linear distortions, rendering global alignment ineffective. By employing edge-aware, regionally smooth fields and a normal-aware regularizer, AffineGS aligns disparity with 3DGS depth and normals, achieving strong photometric quality while significantly enhancing geometry across diverse experiments.

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