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 271–280 of 408 papers

TitleStatusHype
TransCamP: Graph Transformer for 6-DoF Camera Pose Estimation—0
Transformer Guided Geometry Model for Flow-Based Unsupervised Visual Odometry—0
Two Stream Networks for Self-Supervised Ego-Motion Estimation—0
UFM: A Simple Path towards Unified Dense Correspondence with Flow—0
Uncertainty-Aware Camera Pose Estimation from Points and Lines—0
UnDeepVO: Monocular Visual Odometry through Unsupervised Deep Learning—0
UnRectDepthNet: Self-Supervised Monocular Depth Estimation using a Generic Framework for Handling Common Camera Distortion Models—0
Unsupervised Collaborative Learning of Keyframe Detection and Visual Odometry Towards Monocular Deep SLAM—0
Unsupervised Deep Persistent Monocular Visual Odometry and Depth Estimation in Extreme Environments—0
Unsupervised Learning of Depth and Deep Representation for Visual Odometry from Monocular Videos in a Metric Space—0
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Benchmark Results

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