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 131–140 of 408 papers

TitleStatusHype
D3VO: Deep Depth, Deep Pose and Deep Uncertainty for Monocular Visual Odometry—0
eStonefish-scenes: A synthetically generated dataset for underwater event-based optical flow prediction tasks—0
cuVSLAM: CUDA accelerated visual odometry and mapping—0
A Review of Visual Odometry Methods and Its Applications for Autonomous Driving—0
Epipolar Geometry based Learning of Multi-view Depth and Ego-Motion from Monocular Sequences—0
Enhancing self-supervised monocular depth estimation with traditional visual odometry—0
Creating a Segmented Pointcloud of Grapevines by Combining Multiple Viewpoints Through Visual Odometry—0
EMR-MSF: Self-Supervised Recurrent Monocular Scene Flow Exploiting Ego-Motion Rigidity—0
Approaches, Challenges, and Applications for Deep Visual Odometry: Toward to Complicated and Emerging Areas—0
E-Graph: Minimal Solution for Rigid Rotation with Extensibility Graphs—0
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Benchmark Results

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