SOTAVerified

Visual Odometry

Visual Odometry is an important area of information fusion in which the central aim is to estimate the pose of a robot using data collected by visual sensors.

Source: Bi-objective Optimization for Robust RGB-D Visual Odometry

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 161–170 of 408 papers

TitleStatusHype
Mind the Gap! A Study on the Transferability of Virtual vs Physical-world Testing of Autonomous Driving SystemsCode0
360-DFPE: Leveraging Monocular 360-Layouts for Direct Floor Plan EstimationCode1
GreenPCO: An Unsupervised Lightweight Point Cloud Odometry Method—0
3D Hierarchical Refinement and Augmentation for Unsupervised Learning of Depth and Pose from Monocular Video—0
Learning Generalized Visual Odometry Using Position-Aware Optical Flow and Geometric Bundle Adjustment—0
TANDEM: Tracking and Dense Mapping in Real-time using Deep Multi-view StereoCode1
MC-CIM: Compute-in-Memory with Monte-Carlo Dropouts for Bayesian Edge Intelligence—0
MSC-VO: Exploiting Manhattan and Structural Constraints for Visual Odometry—0
Robust Edge-Direct Visual Odometry based on CNN edge detection and Shi-Tomasi corner optimization—0
Attentive and Contrastive Learning for Joint Depth and Motion Field Estimation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CIVORelative Position Error Translation [cm]1.36—Unverified