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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 201–210 of 408 papers

TitleStatusHype
Canny-VO: Visual Odometry with RGB-D Cameras based on Geometric 3D-2D Edge Alignment—0
Transformer Guided Geometry Model for Flow-Based Unsupervised Visual Odometry—0
Online Photometric Calibration of Automatic Gain Thermal Infrared CamerasCode1
Depth Completion using Piecewise Planar Model—0
Exploring Self-Attention for Visual Odometry—0
EffiScene: Efficient Per-Pixel Rigidity Inference for Unsupervised Joint Learning of Optical Flow, Depth, Camera Pose and Motion Segmentation—0
TartanVO: A Generalizable Learning-based VOCode1
Unsupervised Deep Persistent Monocular Visual Odometry and Depth Estimation in Extreme Environments—0
Empty Cities: a Dynamic-Object-Invariant Space for Visual SLAMCode1
On Deep Learning Techniques to Boost Monocular Depth Estimation for Autonomous Navigation—0
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Benchmark Results

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