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 151–160 of 408 papers

TitleStatusHype
Towards Scale Consistent Monocular Visual Odometry by Learning from the Virtual World—0
A high-precision self-supervised monocular visual odometry in foggy weather based on robust cycled generative adversarial networks and multi-task learning aided depth estimation—0
Asynchronous Optimisation for Event-based Visual Odometry—0
Vision-based Large-scale 3D Semantic Mapping for Autonomous Driving Applications—0
Efficient Globally-Optimal Correspondence-Less Visual Odometry for Planar Ground Vehicles—0
LF-VIO: A Visual-Inertial-Odometry Framework for Large Field-of-View Cameras with Negative PlaneCode1
DEVO: Depth-Event Camera Visual Odometry in Challenging Conditions—0
Benchmarking Pedestrian Odometry: The Brown Pedestrian Odometry Dataset (BPOD)—0
Multi-Camera Sensor Fusion for Visual Odometry using Deep Uncertainty Estimation—0
MDN-VO: Estimating Visual Odometry with Confidence—0
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Benchmark Results

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