StereoGS: Sparse-View 3D Gaussian Splatting via Stereo Priors

• URL: http://arxiv.org/abs/2606.30545v2
• Date: Sun, 05 Jul 2026 02:47:54 GMT
• Title: StereoGS: Sparse-View 3D Gaussian Splatting via Stereo Priors
• Abstract summary: 3D Gaussian Splatting (3DGS) has achieved remarkable success in real-time novel view synthesis.<n>It suffers from severe overfitting under sparse-view settings due to insufficient geometric constraints.<n>We propose StereoGS, a novel sparse-view 3DGS framework that integrates stereo priors to establish reliable binocular consistency.
• Score: 0.9326260051834822
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 3D Gaussian Splatting (3DGS) has achieved remarkable success in real-time novel view synthesis, yet it suffers from severe overfitting under sparse-view settings due to insufficient geometric constraints. While recent methods introduce monocular depth priors to mitigate this, they inherently struggle with scale ambiguity and cross-view inconsistency, leading to defective geometry. In this paper, we propose StereoGS, a novel sparse-view 3DGS framework that integrates stereo priors to establish reliable binocular consistency. Unlike scale-agnostic monocular constraints, StereoGS introduces a Stereo Depth Regularization by constructing virtual stereo pairs during optimization and leveraging a foundation stereo model to enforce absolute scale and binocular-consistent structures. To further suppress overfitting and eliminate redundant primitives, we design a Gradient-Aware Opacity Decay strategy that dynamically penalizes Gaussians based on their relative opacity gradient magnitudes. Combined with a Consistency-Aware Dense Initialization using zero-shot multi-view depth estimation, StereoGS effectively anchors primitives to accurate scene surfaces. Extensive experiments on LLFF, DTU, Mip-NeRF360, and Blender datasets demonstrate that StereoGS achieves state-of-the-art performance in sparse-view settings without incurring any additional inference overhead. Project Page: https://stringerywh00.github.io/StereoGS_project_page/

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