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 281–290 of 408 papers

TitleStatusHype
VSO: Visual Semantic Odometry—0
What My Motion tells me about Your Pose: A Self-Supervised Monocular 3D Vehicle Detector—0
XVO: Generalized Visual Odometry via Cross-Modal Self-Training—0
ZeroVO: Visual Odometry with Minimal Assumptions—0
3D Hierarchical Refinement and Augmentation for Unsupervised Learning of Depth and Pose from Monocular Video—0
4DRVO-Net: Deep 4D Radar-Visual Odometry Using Multi-Modal and Multi-Scale Adaptive Fusion—0
4Seasons: A Cross-Season Dataset for Multi-Weather SLAM in Autonomous Driving—0
4Seasons: Benchmarking Visual SLAM and Long-Term Localization for Autonomous Driving in Challenging Conditions—0
Accurate and Robust Scale Recovery for Monocular Visual Odometry Based on Plane Geometry—0
A Combined Approach Toward Consistent Reconstructions of Indoor Spaces Based on 6D RGB-D Odometry and KinectFusion—0
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Benchmark Results

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