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 121–130 of 408 papers

TitleStatusHype
Motion Consistency Loss for Monocular Visual Odometry with Attention-Based Deep Learning—0
Trajectory Approximation of Video Based on Phase Correlation for Forward Facing Camera—0
Brain-Inspired Visual Odometry: Balancing Speed and Interpretability through a System of Systems ApproachCode0
NeRF-VO: Real-Time Sparse Visual Odometry with Neural Radiance Fields—0
Ternary-Type Opacity and Hybrid Odometry for RGB NeRF-SLAM—0
Loss it right: Euclidean and Riemannian Metrics in Learning-based Visual OdometryCode0
SuperPrimitive: Scene Reconstruction at a Primitive Level—0
Dense Visual Odometry Using Genetic Algorithm—0
Inertial Guided Uncertainty Estimation of Feature Correspondence in Visual-Inertial Odometry/SLAM—0
Resilient Simultaneous Localization and Mapping Fusing Ultra Wide Band Range Measurements and Visual Odometry—0
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Benchmark Results

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