Monocular Visual Odometry
18 papers with code • 0 benchmarks • 6 datasets
Benchmarks
These leaderboards are used to track progress in Monocular Visual Odometry
Datasets
TUM monoVO
EndoSLAM
ConsInv Dataset
Drunkard's Dataset
VBR
Bike and Car Odometer Dataset ! Speedometer OCR
Latest papers with no code
Deep Online Correction for Monocular Visual Odometry
Second, the poses predicted by CNNs are further improved by minimizing photometric errors via gradient updates of poses during inference phases.
Accurate and Robust Scale Recovery for Monocular Visual Odometry Based on Plane Geometry
In this paper, with the assumption of a constant height of the camera above the ground, we develop a light-weight scale recovery framework leveraging an accurate and robust estimation of the ground plane.
Unsupervised Deep Persistent Monocular Visual Odometry and Depth Estimation in Extreme Environments
In recent years, unsupervised deep learning approaches have received significant attention to estimate the depth and visual odometry (VO) from unlabelled monocular image sequences.
Deep Monocular Visual Odometry for Ground Vehicle
To push the limit, we analyze the motion pattern of a ground vehicle and focus on learning two-degrees-of-freedom motions by proposed motion focusing and decoupling.
What My Motion tells me about Your Pose: A Self-Supervised Monocular 3D Vehicle Detector
We subsequently demonstrate an optimization-based monocular 3D bounding box detector built on top of the self-supervised vehicle orientation estimator without the requirement of expensive labeled data.
Learning Monocular Visual Odometry via Self-Supervised Long-Term Modeling
Monocular visual odometry (VO) suffers severely from error accumulation during frame-to-frame pose estimation.
Virtual Testbed for Monocular Visual Navigation of Small Unmanned Aircraft Systems
Monocular visual navigation methods have seen significant advances in the last decade, recently producing several real-time solutions for autonomously navigating small unmanned aircraft systems without relying on GPS.
D3VO: Deep Depth, Deep Pose and Deep Uncertainty for Monocular Visual Odometry
We propose D3VO as a novel framework for monocular visual odometry that exploits deep networks on three levels -- deep depth, pose and uncertainty estimation.
AD-VO: Scale-Resilient Visual Odometry Using Attentive Disparity Map
Visual odometry is an essential key for a localization module in SLAM systems.
ViLiVO: Virtual LiDAR-Visual Odometry for an Autonomous Vehicle with a Multi-Camera System
As for the pose tracker, we propose a visual odometry system fusing both the feature matching and the virtual LiDAR scan matching results.
