TIDI-GS: Floater Suppression in 3D Gaussian Splatting for Enhanced Indoor Scene Fidelity
Sooyeun Yang, Cheyul Im, Jee Won Lee, and Jongseong Brad Choi

TL;DR
TIDI-GS is a lightweight training framework that effectively removes floaters in 3D Gaussian Splatting, significantly improving scene fidelity and geometric accuracy without major architectural changes.
Contribution
We introduce TIDI-GS, a novel floater pruning method integrated into 3D Gaussian Splatting that enhances scene quality by eliminating artifacts while preserving details.
Findings
Reduces floaters and improves scene fidelity.
Enhances geometric accuracy of 3D reconstructions.
Maintains high-frequency details during cleanup.
Abstract
3D Gaussian Splatting (3DGS) is a technique to create high-quality, real-time 3D scenes from images. This method often produces visual artifacts known as floaters--nearly transparent, disconnected elements that drift in space away from the actual surface. This geometric inaccuracy undermines the reliability of these models for practical applications, which is critical. To address this issue, we introduce TIDI-GS, a new training framework designed to eliminate these floaters. A key benefit of our approach is that it functions as a lightweight plugin for the standard 3DGS pipeline, requiring no major architectural changes and adding minimal overhead to the training process. The core of our method is a floater pruning algorithm--TIDI--that identifies and removes floaters based on several criteria: their consistency across multiple viewpoints, their spatial relationship to other elements,…
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Taxonomy
TopicsAdvanced Vision and Imaging · 3D Shape Modeling and Analysis · Image Enhancement Techniques
