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
Ground Plane based Absolute Scale Estimation for Monocular Visual Odometry—0
Deep Visual Odometry Methods for Mobile Robots—0
Gradient-based Camera Exposure Control for Outdoor Mobile Platforms—0
GreenPCO: An Unsupervised Lightweight Point Cloud Odometry Method—0
Deep Virtual Stereo Odometry: Leveraging Deep Depth Prediction for Monocular Direct Sparse Odometry—0
DeepVO: A Deep Learning approach for Monocular Visual Odometry—0
A Combined Approach Toward Consistent Reconstructions of Indoor Spaces Based on 6D RGB-D Odometry and KinectFusion—0
Inertial Guided Uncertainty Estimation of Feature Correspondence in Visual-Inertial Odometry/SLAM—0
Global Pose Estimation with an Attention-based Recurrent Network—0
Geometry-Constrained Monocular Scale Estimation Using Semantic Segmentation for Dynamic Scenes—0
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Benchmark Results

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