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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 326–350 of 408 papers

TitleStatusHype
D3VO: Deep Depth, Deep Pose and Deep Uncertainty for Monocular Visual Odometry—0
DeepAVO: Efficient Pose Refining with Feature Distilling for Deep Visual Odometry—0
Deep Direct Visual Odometry—0
Deep EndoVO: A Recurrent Convolutional Neural Network (RCNN) based Visual Odometry Approach for Endoscopic Capsule Robots—0
Deep Feature Tracker: A Novel Application for Deep Convolutional Neural Networks—0
Deep Global-Relative Networks for End-to-End 6-DoF Visual Localization and Odometry—0
Deep Learning for Visual Localization and Mapping: A Survey—0
Deep Monocular Visual Odometry for Ground Vehicle—0
Deep Online Correction for Monocular Visual Odometry—0
DeepPCO: End-to-End Point Cloud Odometry through Deep Parallel Neural Network—0
DeepTIO: A Deep Thermal-Inertial Odometry with Visual Hallucination—0
Deep Virtual Stereo Odometry: Leveraging Deep Depth Prediction for Monocular Direct Sparse Odometry—0
Deep Visual Odometry Methods for Mobile Robots—0
DeepVO: A Deep Learning approach for Monocular Visual Odometry—0
Dense Piecewise Planar RGB-D SLAM for Indoor Environments—0
Dense Visual Odometry Using Genetic Algorithm—0
Depth Completion using Piecewise Planar Model—0
DEVO: Depth-Event Camera Visual Odometry in Challenging Conditions—0
DINO-VO: A Feature-based Visual Odometry Leveraging a Visual Foundation Model—0
Direct Monocular Odometry Using Points and Lines—0
Direct Sparse Odometry with Rolling Shutter—0
DirectTracker: 3D Multi-Object Tracking Using Direct Image Alignment and Photometric Bundle Adjustment—0
Direct Visual-Inertial Odometry with Semi-Dense Mapping—0
Discovering Multiple Algorithm Configurations—0
Distilling Knowledge From a Deep Pose Regressor Network—0
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Benchmark Results

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