7 citations · 14 across the 10 of their papers we have counts for
6 papers · 1 filter
AGS-Mesh: Adaptive Gaussian Splatting and Meshing with Geometric Priors for Indoor Room Reconstruction Using Smartphones
Xuqian Ren, Matias Turkulainen, Jiepeng Wang +4
Geometric priors are often used to enhance 3D reconstruction. With many smartphones featuring low-resolution depth sensors and the prevalence of off-the-shelf monocular geometry es…
DeSplat: Decomposed Gaussian Splatting for Distractor-Free Rendering
Yihao Wang, Marcus Klasson, Matias Turkulainen +3
Gaussian splatting enables fast novel view synthesis in static 3D environments. However, reconstructing real-world environments remains challenging as distractors or occluders brea…
Gaussian Splatting in Mirrors: Reflection-Aware Rendering via Virtual Camera Optimization
Zihan Wang, Shuzhe Wang, Matias Turkulainen +2
Recent advancements in 3D Gaussian Splatting (3D-GS) have revolutionized novel view synthesis, facilitating real-time, high-quality image rendering. However, in scenarios involving…
gsplat: An Open-Source Library for Gaussian Splatting
Vickie Ye, Ruilong Li, Justin Kerr +8
gsplat is an open-source library designed for training and developing Gaussian Splatting methods. It features a front-end with Python bindings compatible with the PyTorch library a…
DN-Splatter: Depth and Normal Priors for Gaussian Splatting and Meshing
Matias Turkulainen, Xuqian Ren, Iaroslav Melekhov +3
High-fidelity 3D reconstruction of common indoor scenes is crucial for VR and AR applications. 3D Gaussian splatting, a novel differentiable rendering technique, has achieved state…
Gaussian Splatting on the Move: Blur and Rolling Shutter Compensation for Natural Camera Motion
Otto Seiskari, Jerry Ylilammi, Valtteri Kaatrasalo +5
High-quality scene reconstruction and novel view synthesis based on Gaussian Splatting (3DGS) typically require steady, high-quality photographs, often impractical to capture with…