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 61–70 of 408 papers

TitleStatusHype
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
A Smooth Representation of Belief over SO(3) for Deep Rotation Learning with UncertaintyCode1
Towards Better Generalization: Joint Depth-Pose Learning without PoseNetCode1
Nonparametric Continuous Sensor RegistrationCode1
Visual Odometry Revisited: What Should Be Learnt?Code1
Unsupervised Scale-consistent Depth and Ego-motion Learning from Monocular VideoCode1
UnOS: Unified Unsupervised Optical-Flow and Stereo-Depth Estimation by Watching VideosCode1
The TUM VI Benchmark for Evaluating Visual-Inertial OdometryCode1
ORB-SLAM2: an Open-Source SLAM System for Monocular, Stereo and RGB-D CamerasCode1
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Benchmark Results

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