SOTAVerified

Simultaneous Localization and Mapping

Simultaneous localization and mapping (SLAM) is the task of constructing or updating a map of an unknown environment while simultaneously keeping track of an agent's location within it.

( Image credit: ORB-SLAM2 )

Papers

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Showing 21–30 of 572 papers

TitleStatusHype
Customizable Perturbation Synthesis for Robust SLAM BenchmarkingCode2
Advancing Dense Endoscopic Reconstruction with Gaussian Splatting-driven Surface Normal-aware Tracking and MappingCode2
GlORIE-SLAM: Globally Optimized RGB-only Implicit Encoding Point Cloud SLAMCode2
BoW3D: Bag of Words for Real-Time Loop Closing in 3D LiDAR SLAMCode2
GV-Bench: Benchmarking Local Feature Matching for Geometric Verification of Long-term Loop Closure DetectionCode2
FlexCloud: Direct, Modular Georeferencing and Drift-Correction of Point Cloud MapsCode2
3D Dynamic Scene Graphs: Actionable Spatial Perception with Places, Objects, and HumansCode2
Event-based Stereo Depth Estimation: A SurveyCode2
Open-Vocabulary Online Semantic Mapping for SLAMCode2
From Perfect to Noisy World Simulation: Customizable Embodied Multi-modal Perturbations for SLAM Robustness BenchmarkingCode2
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