19 citations · 32 across the 8 of their papers we have counts for
5 papers · 1 filter
LoopSplat: Loop Closure by Registering 3D Gaussian Splats
Liyuan Zhu, Yue Li, Erik Sandström +3
Simultaneous Localization and Mapping (SLAM) based on 3D Gaussian Splats (3DGS) has recently shown promise towards more accurate, dense 3D scene maps. However, existing 3DGS-based…
VF-NeRF: Learning Neural Vector Fields for Indoor Scene Reconstruction
Albert Gassol Puigjaner, Edoardo Mello Rella, Erik Sandström +2
Implicit surfaces via neural radiance fields (NeRF) have shown surprising accuracy in surface reconstruction. Despite their success in reconstructing richly textured surfaces, exis…
Splat-SLAM: Globally Optimized RGB-only SLAM with 3D Gaussians
Erik Sandström, Keisuke Tateno, Michael Oechsle +4
3D Gaussian Splatting has emerged as a powerful representation of geometry and appearance for RGB-only dense Simultaneous Localization and Mapping (SLAM), as it provides a compact…
GlORIE-SLAM: Globally Optimized RGB-only Implicit Encoding Point Cloud SLAM
Ganlin Zhang, Erik Sandström, Youmin Zhang +3
Recent advancements in RGB-only dense Simultaneous Localization and Mapping (SLAM) have predominantly utilized grid-based neural implicit encodings and/or struggle to efficiently r…
Loopy-SLAM: Dense Neural SLAM with Loop Closures
Lorenzo Liso, Erik Sandström, Vladimir Yugay +2
Neural RGBD SLAM techniques have shown promise in dense Simultaneous Localization And Mapping (SLAM), yet face challenges such as error accumulation during camera tracking resultin…