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 231–240 of 408 papers

TitleStatusHype
UnRectDepthNet: Self-Supervised Monocular Depth Estimation using a Generic Framework for Handling Common Camera Distortion Models—0
Virtual Testbed for Monocular Visual Navigation of Small Unmanned Aircraft Systems—0
EndoSLAM Dataset and An Unsupervised Monocular Visual Odometry and Depth Estimation Approach for Endoscopic Videos: Endo-SfMLearnerCode1
Robot Perception enables Complex Navigation Behavior via Self-Supervised LearningCode1
Information-Driven Direct RGB-D Odometry—0
A Smooth Representation of Belief over SO(3) for Deep Rotation Learning with UncertaintyCode1
Self-Supervised Deep Visual Odometry with Online Adaptation—0
BIT-VO: Visual Odometry at 300 FPS using Binary Features from the Focal Plane—0
Masked GANs for Unsupervised Depth and Pose Prediction with Scale Consistency—0
Beyond Photometric Consistency: Gradient-based Dissimilarity for Improving Visual Odometry and Stereo Matching—0
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Benchmark Results

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