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 61–70 of 572 papers

TitleStatusHype
Kimera: an Open-Source Library for Real-Time Metric-Semantic Localization and MappingCode1
Graph-based Thermal-Inertial SLAM with Probabilistic Neural NetworksCode1
iSLAM: Imperative SLAMCode1
LCDNet: Deep Loop Closure Detection and Point Cloud Registration for LiDAR SLAMCode1
AdaptSLAM: Edge-Assisted Adaptive SLAM with Resource Constraints via Uncertainty MinimizationCode1
Embracing Dynamics: Dynamics-aware 4D Gaussian Splatting SLAMCode1
LCP-Fusion: A Neural Implicit SLAM with Enhanced Local Constraints and Computable PriorCode1
LoGG3D-Net: Locally Guided Global Descriptor Learning for 3D Place RecognitionCode1
Deep Depth Estimation from Visual-Inertial SLAMCode1
Deep Keypoint-Based Camera Pose Estimation with Geometric ConstraintsCode1
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