collaborators

5 papers

cs.RO2026

Multi-Resolution Voxelized Map-Based Stereo Visual-Inertial Odometry

Shuyi Pan, Hangtian Wang, Zhaoxing Zhang +3

Incorporating prior maps significantly enhances the accuracy and robustness of pose estimation in visual-inertial odometry (VIO). However, the large data volume of such maps, combi…

cs.CV2025

BAT: Learning Event-based Optical Flow with Bidirectional Adaptive Temporal Correlation

Gangwei Xu, Haotong Lin, Zhaoxing Zhang +3

Event cameras deliver visual information characterized by a high dynamic range and high temporal resolution, offering significant advantages in estimating optical flow for complex…

cs.RO2025

Event-based Stereo Visual-Inertial Odometry with Voxel Map

Zhaoxing Zhang, Xiaoxiang Wang, Chengliang Zhang +3

The event camera, renowned for its high dynamic range and exceptional temporal resolution, is recognized as an important sensor for visual odometry. However, the inherent noise in…

cs.CV2025

RoMeO: Robust Metric Visual Odometry

Junda Cheng, Zhipeng Cai, Zhaoxing Zhang +4

Visual odometry (VO) aims to estimate camera poses from visual inputs -- a fundamental building block for many applications such as VR/AR and robotics. This work focuses on monocul…

cs.CV2025

Leveraging Consistent Spatio-Temporal Correspondence for Robust Visual Odometry

Zhaoxing Zhang, Junda Cheng, Gangwei Xu +3

Recent approaches to VO have significantly improved performance by using deep networks to predict optical flow between video frames. However, existing methods still suffer from noi…