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 231–240 of 408 papers

TitleStatusHype
Some Aspects of Geometric Computer Vision for Analysing Dynamical Scenes focusing Automotive Applications—0
Sparse2Dense: From direct sparse odometry to dense 3D reconstruction—0
SPLODE: Semi-Probabilistic Point and Line Odometry with Depth Estimation from RGB-D Camera Motion—0
SPOT: Point Cloud Based Stereo Visual Place Recognition for Similar and Opposing Viewpoints—0
Stereo-based Multi-motion Visual Odometry for Mobile Robots—0
Stereo DSO: Large-Scale Direct Sparse Visual Odometry with Stereo Cameras—0
Stereo Visual Odometry with Deep Learning-Based Point and Line Feature Matching using an Attention Graph Neural Network—0
Structureless VIO—0
SuperPrimitive: Scene Reconstruction at a Primitive Level—0
Swipe Mosaics from Video—0
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Benchmark Results

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