16 citations · 29 across the 11 of their papers we have counts for
14 papers
Unblur-SLAM: Dense Neural SLAM for Blurry Inputs
Qi Zhang, Denis Rozumny, Francesco Girlanda +4
We propose Unblur-SLAM, a novel RGB SLAM pipeline for sharp 3D reconstruction from blurred image inputs. In contrast to previous work, our approach is able to handle different type…
Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding
Yue Li, Qi Ma, Runyi Yang +8
While 3DGS has emerged as a high-fidelity scene representation, encoding rich, general-purpose features directly from its primitives remains under-explored. We address this gap by…
IDSplat: Instance-Decomposed 3D Gaussian Splatting for Driving Scenes
Carl Lindström, Mahan Rafidashti, Maryam Fatemi +3
Reconstructing dynamic driving scenes is essential for developing autonomous systems through sensor-realistic simulation. Although recent methods achieve high-fidelity reconstructi…
ProDyG: Progressive Dynamic Scene Reconstruction via Gaussian Splatting from Monocular Videos
Shi Chen, Erik Sandström, Sandro Lombardi +2
Achieving truly practical dynamic 3D reconstruction requires online operation, global pose and map consistency, detailed appearance modeling, and the flexibility to handle both RGB…
SceneSplat++: A Large Dataset and Comprehensive Benchmark for Language Gaussian Splatting
Mengjiao Ma, Qi Ma, Yue Li +10
3D Gaussian Splatting (3DGS) serves as a highly performant and efficient encoding of scene geometry, appearance, and semantics. Moreover, grounding language in 3D scenes has proven…
Gaussian Mapping for Evolving Scenes
Vladimir Yugay, Thies Kersten, Luca Carlone +3
Mapping systems with novel view synthesis (NVS) capabilities, most notably 3D Gaussian Splatting (3DGS), are widely used in computer vision, as well as in various applications, inc…
ToF-Splatting: Dense SLAM using Sparse Time-of-Flight Depth and Multi-Frame Integration
Andrea Conti, Matteo Poggi, Valerio Cambareri +2
Time-of-Flight (ToF) sensors provide efficient active depth sensing at relatively low power budgets; among such designs, only very sparse measurements from low-resolution sensors a…
Splat-LOAM: Gaussian Splatting LiDAR Odometry and Mapping
Emanuele Giacomini, Luca Di Giammarino, Lorenzo De Rebotti +2
LiDARs provide accurate geometric measurements, making them valuable for ego-motion estimation and reconstruction tasks. Although its success, managing an accurate and lightweight…
SceneSplat: Gaussian Splatting-based Scene Understanding with Vision-Language Pretraining
Yue Li, Qi Ma, Runyi Yang +10
Recognizing arbitrary or previously unseen categories is essential for comprehensive real-world 3D scene understanding. Currently, all existing methods rely on 2D or textual modali…
MAGiC-SLAM: Multi-Agent Gaussian Globally Consistent SLAM
Vladimir Yugay, Theo Gevers, Martin R. Oswald
Simultaneous localization and mapping (SLAM) systems with novel view synthesis capabilities are widely used in computer vision, with applications in augmented reality, robotics, an…
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…
How NeRFs and 3D Gaussian Splatting are Reshaping SLAM: a Survey
Fabio Tosi, Youmin Zhang, Ziren Gong +4
Over the past two decades, research in the field of Simultaneous Localization and Mapping (SLAM) has undergone a significant evolution, highlighting its critical role in enabling a…
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…