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 161–170 of 408 papers

TitleStatusHype
Driven to Distraction: Self-Supervised Distractor Learning for Robust Monocular Visual Odometry in Urban Environments—0
Drift Reduction for Monocular Visual Odometry of Intelligent Vehicles using Feedforward Neural Networks—0
CFORB: Circular FREAK-ORB Visual Odometry—0
DLO: Direct LiDAR Odometry for 2.5D Outdoor Environment—0
Canny-VO: Visual Odometry with RGB-D Cameras based on Geometric 3D-2D Edge Alignment—0
An Attention-Based Deep Learning Architecture for Real-Time Monocular Visual Odometry: Applications to GPS-free Drone Navigation—0
AD-VO: Scale-Resilient Visual Odometry Using Attentive Disparity Map—0
4Seasons: A Cross-Season Dataset for Multi-Weather SLAM in Autonomous Driving—0
Dive Deeper into Rectifying Homography for Stereo Camera Online Self-Calibration—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