2D Gaussian Splatting for Geometrically Accurate Radiance Fields

2024-03-26

International Conference on Computer Graphics and Interactive Techniques

AI Summary

To address the challenge of inaccurate surface reconstruction in 3D Gaussian Splatting (3DGS) caused by multi-view geometric inconsistency, this paper proposes 2D Gaussian Splatting: modeling voxels as oriented planar Gaussian disks to achieve geometrically consistent radiance field reconstruction. Methodologically, we introduce ray-Gaussian intersection–driven perspective-correct splatting, jointly optimized with depth distortion regularization and normal consistency loss to enforce geometric and appearance coherence. Leveraging differentiable 2D splatting rendering and multi-view geometric regularization, our approach preserves real-time rendering performance while significantly improving stability in reconstructing thin structures and enhancing surface accuracy. The result is noise-free, high-fidelity geometric reconstructions with fine geometric detail and competitive appearance quality.

Technology Category

• Computer Vision: 3D Computer Vision
• Knowledge Representation and Reasoning: Geometric, Spatial, and Temporal Reasoning
• Planning, Routing, and Scheduling: Replanning and Plan Repair

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking
• Systems and Infrastructure for Web, Mobile and WoT: Sustainability and carbon-aware systems for Web, mobile, and WoT

Abstract

3D Gaussian Splatting (3DGS) has recently revolutionized radiance field reconstruction, achieving high quality novel view synthesis and fast rendering speed without baking. However, 3DGS fails to accurately represent surfaces due to the multi-view inconsistent nature of 3D Gaussians. We present 2D Gaussian Splatting (2DGS), a novel approach to model and reconstruct geometrically accurate radiance fields from multi-view images. Our key idea is to collapse the 3D volume into a set of 2D oriented planar Gaussian disks. Unlike 3D Gaussians, 2D Gaussians provide view-consistent geometry while modeling surfaces intrinsically. To accurately recover thin surfaces and achieve stable optimization, we introduce a perspective-correct 2D splatting process utilizing ray-splat intersection and rasterization. Additionally, we incorporate depth distortion and normal consistency terms to further enhance the quality of the reconstructions. We demonstrate that our differentiable renderer allows for noise-free and detailed geometry reconstruction while maintaining competitive appearance quality, fast training speed, and real-time rendering.

Problem

• Improve surface representation accuracy
• Enhance thin surface reconstruction
• Maintain fast rendering speed

Innovation

• 2D Gaussian disks
• perspective-correct splatting
• depth distortion enhancement