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 361–370 of 408 papers

TitleStatusHype
Efficient Domain Adaptation for Endoscopic Visual Odometry—0
Efficient Globally-Optimal Correspondence-Less Visual Odometry for Planar Ground Vehicles—0
EffiScene: Efficient Per-Pixel Rigidity Inference for Unsupervised Joint Learning of Optical Flow, Depth, Camera Pose and Motion Segmentation—0
E-Graph: Minimal Solution for Rigid Rotation with Extensibility Graphs—0
EMR-MSF: Self-Supervised Recurrent Monocular Scene Flow Exploiting Ego-Motion Rigidity—0
Enhancing self-supervised monocular depth estimation with traditional visual odometry—0
Epipolar Geometry based Learning of Multi-view Depth and Ego-Motion from Monocular Sequences—0
eStonefish-scenes: A synthetically generated dataset for underwater event-based optical flow prediction tasks—0
Evaluation of the visual odometry methods for semi-dense real-time—0
Event-aided Direct Sparse Odometry—0
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Benchmark Results

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