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
Deep Visual Odometry with Events and FramesCode1
Unsupervised Scale-consistent Depth and Ego-motion Learning from Monocular VideoCode1
Online Photometric Calibration of Automatic Gain Thermal Infrared CamerasCode1
A Smooth Representation of Belief over SO(3) for Deep Rotation Learning with UncertaintyCode1
Deep Event Visual OdometryCode1
Dense Prediction Transformer for Scale Estimation in Monocular Visual OdometryCode1
DF-VO: What Should Be Learnt for Visual Odometry?Code1
Deep Keypoint-Based Camera Pose Estimation with Geometric ConstraintsCode1
RAM-VO: Less is more in Visual OdometryCode1
SF2SE3: Clustering Scene Flow into SE(3)-Motions via Proposal and SelectionCode1
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Benchmark Results

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