3D Gaussian Splatting with Fisheye Images: Field of View Analysis and Depth-Based Initialization

We present the first evaluation of 3D Gaussian Splatting methods on real fisheye imagery with fields of view above 180textdegree. Our study evaluates Fisheye-GS citeliao2024fisheyegslightweightextensiblegaussian and 3DGUT citewu20253dgut on indoor and outdoor scenes captured with 200textdegree fisheye cameras, with the aim of assessing the practicality of wide-angle reconstruction under severe distortion. By comparing reconstructions at 200textdegree, 160textdegree, and 120textdegree field-of-view, we show that both methods achieve their best results at 160textdegree, which balances scene coverage with image quality, while distortion at 200textdegree degrades performance. To address the common failure of Structure-from-Motion (SfM) initialization at such wide angles, we introduce a depth-based alternative using UniK3D (Universal Camera Monocular 3D Estimation) citepiccinelli2025unik3d. This represents the first application of UniK3D to fisheye imagery beyond 200textdegree, despite the model not being trained on such data. With the number of predicted points controlled to match SfM for fairness, UniK3D produces geometrically accurate reconstructions that rival or surpass SfM, even in challenging scenes with fog, glare, or open sky. These results demonstrate the feasibility of fisheye-based 3D Gaussian Splatting and provides a benchmark for future research on wide-angle reconstruction from sparse and distorted inputs.