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 141–150 of 572 papers

TitleStatusHype
VTGaussian-SLAM: RGBD SLAM for Large Scale Scenes with Splatting View-Tied 3D Gaussians—0
Black-box Adversarial Attacks on CNN-based SLAM Algorithms—0
UP-SLAM: Adaptively Structured Gaussian SLAM with Uncertainty Prediction in Dynamic Environments—0
Visual Loop Closure Detection Through Deep Graph Consensus—0
ADD-SLAM: Adaptive Dynamic Dense SLAM with Gaussian Splatting—0
SafeNav: Safe Path Navigation using Landmark Based Localization in a GPS-denied Environment—0
EdgePoint2: Compact Descriptors for Superior Efficiency and Accuracy—0
DERD-Net: Learning Depth from Event-based Ray DensitiesCode0
SLAM&Render: A Benchmark for the Intersection Between Neural Rendering, Gaussian Splatting and SLAMCode0
PNE-SGAN: Probabilistic NDT-Enhanced Semantic Graph Attention Network for LiDAR Loop Closure Detection—0
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