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 191–200 of 408 papers

TitleStatusHype
Geometry-Constrained Monocular Scale Estimation Using Semantic Segmentation for Dynamic Scenes—0
DeepTIO: A Deep Thermal-Inertial Odometry with Visual Hallucination—0
Geometric Consistency for Self-Supervised End-to-End Visual Odometry—0
Geometric-based Line Segment Tracking for HDR Stereo Sequences—0
Lightweight, Uncertainty-Aware Conformalized Visual Odometry—0
DeepPCO: End-to-End Point Cloud Odometry through Deep Parallel Neural Network—0
LiVisSfM: Accurate and Robust Structure-from-Motion with LiDAR and Visual Cues—0
Local Supports Global: Deep Camera Relocalization with Sequence Enhancement—0
LOF: Structure-Aware Line Tracking based on Optical Flow—0
A Unified Formulation for Visual Odometry—0
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Benchmark Results

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