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

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Showing 211–220 of 408 papers

TitleStatusHype
Scale-Awareness of Light Field Camera based Visual Odometry—0
Scale Recovery for Monocular Visual Odometry Using Depth Estimated With Deep Convolutional Neural Fields—0
Scene-agnostic Pose Regression for Visual Localization—0
Scene Motion Decomposition for Learnable Visual Odometry—0
Secure Navigation using Landmark-based Localization in a GPS-denied Environment—0
Self-Improving Visual Odometry—0
Self-Supervised Deep Visual Odometry with Online Adaptation—0
Self-supervised Pretraining and Finetuning for Monocular Depth and Visual Odometry—0
Self-Supervised Steering Angle Prediction for Vehicle Control Using Visual Odometry—0
Semantic Nearest Neighbor Fields Monocular Edge Visual-Odometry—0
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Benchmark Results

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