Deep Patch Visual Odometry

Deep Patch Visual Odometry Information Guide

1. About of Deep Patch Visual Odometry
2. Main Features
3. Developments
4. Deep Dive
5. Summary

About of Deep Patch Visual Odometry

Authors: Shunkai Li, Xin Wang, Yingdian Cao, Fei Xue, Zike Yan, Hongbin Zha Description: Self-supervised VO methods have ... Authors: Nan Yang, Lukas von Stumberg, Rui Wang, Daniel Cremers Description: We propose D3VO as a novel framework for ... Event-based cameras are bio-inspired sensors with pixels that independently and asynchronously respond to brightness changes ... This video is a demo for our work (Accepted to ICRA-2020) that using Presentation by Yafei Hu, part of the AirLab Summer School 2020. Sessions list, overviews, and links to repos: ...

Main Features

Developments

Stereo-DEVO: Deep Visual Odometry with Stereo Event Cameras (RA-L 2025)

[CVPR 2026] OpenVO: Open-World Visual Odometry with Temporal Dynamics Awareness

Unsupervised Deep Persistent Monocular Visual Odometry and Depth Estimation in Extreme Environments

D3VO: Deep Depth, Deep Pose and Deep Uncertainty for Monocular Visual Odometry

RC Car Visual Odometry

Visual Odometry Revisited: What Should Be Learnt

1-Minute Talk - Learning Monocular Visual Odometry via Self-Supervised Long-Term Modeling

Monocular Visual Odometry

Feature-based, Direct, and Deep Learning Methods of Visual Odometry

Deep Dive

Data is compiled from public records and verified media reports.

Last Updated: June 13, 2026

Summary

Disclaimer: Disclaimer: Details estimates are based on publicly available data, media reports, and financial analysis. Actual numbers may vary.