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 91–100 of 408 papers

TitleStatusHype
Leveraging Consistent Spatio-Temporal Correspondence for Robust Visual OdometryCode0
RoMeO: Robust Metric Visual Odometry—0
eCARLA-scenes: A synthetically generated dataset for event-based optical flow predictionCode0
An indoor DSO-based ceiling-vision odometry system for indoor industrial environments—0
InCrowd-VI: A Realistic Visual-Inertial Dataset for Evaluating SLAM in Indoor Pedestrian-Rich Spaces for Human NavigationCode0
Robust Monocular Visual Odometry using Curriculum Learning—0
MPVO: Motion-Prior based Visual Odometry for PointGoal Navigation—0
LiVisSfM: Accurate and Robust Structure-from-Motion with LiDAR and Visual Cues—0
ORB-SfMLearner: ORB-Guided Self-supervised Visual Odometry with Selective Online Adaptation—0
MAC-VO: Metrics-aware Covariance for Learning-based Stereo Visual Odometry—0
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Benchmark Results

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