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 261–270 of 408 papers

TitleStatusHype
UnDeepVO: Monocular Visual Odometry through Unsupervised Deep Learning—0
UnRectDepthNet: Self-Supervised Monocular Depth Estimation using a Generic Framework for Handling Common Camera Distortion Models—0
Unsupervised Collaborative Learning of Keyframe Detection and Visual Odometry Towards Monocular Deep SLAM—0
Unsupervised Deep Persistent Monocular Visual Odometry and Depth Estimation in Extreme Environments—0
Unsupervised Learning of Depth and Deep Representation for Visual Odometry from Monocular Videos in a Metric Space—0
Unsupervised Learning of Depth Estimation and Visual Odometry for Sparse Light Field Cameras—0
Unsupervised Visual Odometry and Action Integration for PointGoal Navigation in Indoor Environment—0
ViLiVO: Virtual LiDAR-Visual Odometry for an Autonomous Vehicle with a Multi-Camera System—0
ViPR: Visual-Odometry-aided Pose Regression for 6DoF Camera Localization—0
Virtual Inverse Perspective Mapping for Simultaneous Pose and Motion Estimation—0
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Benchmark Results

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