GSCompleter: A Distillation-Free Plugin for Metric-Aware 3D Gaussian Splatting Completion in Seconds

TL;DR

GSCompleter introduces a fast, stable, and distillation-free method for 3D scene completion in Gaussian Splatting, significantly improving quality and efficiency over prior approaches.

Contribution

It proposes a novel

Findings

Achieves state-of-the-art results on three benchmarks.

Improves completion quality and efficiency over existing methods.

Replaces unstable distillation with rapid geometric registration.

Abstract

3D Gaussian Splatting (3DGS) has revolutionized high-fidelity neural rendering with its explicit representation and efficiency. However, reconstructing scenes from sparse viewpoints suffers from severe geometric voids and floaters due to limited coverage. Current scene completion methods typically rely on an iterative "Repair-then-Distill" paradigm, which is computationally intensive, prone to unstable optimization, and susceptible to overfitting. To address these limitations, we propose GSCompleter, a distillation-free plugin that shifts scene completion to a stable "Generate-then-Register" workflow. Specifically, GSCompleter synthesizes visually plausible 2D reference images and explicitly lifts them into 3D Gaussian primitives with a consistent metric scale via a robust Stereo-Anchor View Selection mechanism. These newly generated primitives are then seamlessly integrated into the global scene using a novel Ray-Constrained Registration strategy. By replacing unstable distillation with rapid geometric registration, GSCompleter exhibits superior 3DGS completion performance across three benchmarks, enhancing both quality and efficiency over various baselines and achieving new state-of-the-art (SOTA) results.