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 151–160 of 408 papers

TitleStatusHype
DynaNet: Neural Kalman Dynamical Model for Motion Estimation and Prediction—0
DynaMiTe: A Dynamic Local Motion Model with Temporal Constraints for Robust Real-Time Feature Matching—0
CodedVO: Coded Visual Odometry—0
A Novel Georeferenced Dataset for Stereo Visual Odometry—0
Dynamic Objects Segmentation for Visual Localization in Urban Environments—0
Dynamic Dense RGB-D SLAM using Learning-based Visual Odometry—0
ClusterVO: Clustering Moving Instances and Estimating Visual Odometry for Self and Surroundings—0
DSVO: Direct Stereo Visual Odometry—0
Challenges in Monocular Visual Odometry: Photometric Calibration, Motion Bias and Rolling Shutter Effect—0
An indoor DSO-based ceiling-vision odometry system for indoor industrial environments—0
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Benchmark Results

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