activity
20242026
collaborators

7 papers

cs.CV2026

Confidence-Based Mesh Extraction from 3D Gaussians

Lukas Radl, Felix Windisch, Andreas Kurz +3

Recently, 3D Gaussian Splatting (3DGS) greatly accelerated mesh extraction from posed images due to its explicit representation and fast software rasterization. While the addition…

cs.GR2026

A LoD of Gaussians: Unified Training and Rendering for Ultra-Large Scale Reconstruction with External Memory

Felix Windisch, Thomas Köhler, Lukas Radl +4

Gaussian Splatting has emerged as a high-performance technique for novel view synthesis, enabling real-time rendering and high-quality reconstruction of small scenes. However, scal…

cs.GR2026

DreamAnywhere: Object-Centric Panoramic 3D Scene Generation

Edoardo Alberto Dominici, Jozef Hladky, Floor Verhoeven +9

Recent advances in text-to-3D scene generation have demonstrated significant potential to transform content creation across multiple industries. Although the research community has…

cs.GR2025

SOF: Sorted Opacity Fields for Fast Unbounded Surface Reconstruction

Lukas Radl, Felix Windisch, Thomas Deixelberger +4

Recent advances in 3D Gaussian representations have significantly improved the quality and efficiency of image-based scene reconstruction. Their explicit nature facilitates real-ti…

cs.GR2025

AAA-Gaussians: Anti-Aliased and Artifact-Free 3D Gaussian Rendering

Michael Steiner, Thomas Köhler, Lukas Radl +3

Although 3D Gaussian Splatting (3DGS) has revolutionized 3D reconstruction, it still faces challenges such as aliasing, projection artifacts, and view inconsistencies, primarily du…

cs.GR2025

VRSplat: Fast and Robust Gaussian Splatting for Virtual Reality

Xuechang Tu, Lukas Radl, Michael Steiner +3

3D Gaussian Splatting (3DGS) has rapidly become a leading technique for novel-view synthesis, providing exceptional performance through efficient software-based GPU rasterization.…