collaborators

6 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.CV2026

Autoregressive Appearance Prediction for 3D Gaussian Avatars

Michael Steiner, Zhang Chen, Alexander Richard +3

A photorealistic and immersive human avatar experience demands capturing fine, person-specific details such as cloth and hair dynamics, subtle facial expressions, and characteristi…

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.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.…