most citedTowards Scale Consistent Monocular Visual Odometry by Learning from the Virtual World

4 citations · 9 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2023

Event-based Simultaneous Localization and Mapping: A Comprehensive Survey

Kunping Huang, Sen Zhang, Jing Zhang +1

In recent decades, visual simultaneous localization and mapping (vSLAM) has gained significant interest in both academia and industry. It estimates camera motion and reconstructs t…

cs.CV2022★ 2 cited

Towards Scale-Aware, Robust, and Generalizable Unsupervised Monocular Depth Estimation by Integrating IMU Motion Dynamics

Sen Zhang, Jing Zhang, Dacheng Tao

Unsupervised monocular depth and ego-motion estimation has drawn extensive research attention in recent years. Although current methods have reached a high up-to-scale accuracy, th…

cs.CV2022★ 1 cited

JPerceiver: Joint Perception Network for Depth, Pose and Layout Estimation in Driving Scenes

Haimei Zhao, Jing Zhang, Sen Zhang +1

Depth estimation, visual odometry (VO), and bird's-eye-view (BEV) scene layout estimation present three critical tasks for driving scene perception, which is fundamental for motion…

cs.CV2022★ 4 cited

Towards Scale Consistent Monocular Visual Odometry by Learning from the Virtual World

Sen Zhang, Jing Zhang, Dacheng Tao

Monocular visual odometry (VO) has attracted extensive research attention by providing real-time vehicle motion from cost-effective camera images. However, state-of-the-art optimiz…

cs.CV2022★ 2 cited

Information-Theoretic Odometry Learning

Sen Zhang, Jing Zhang, Dacheng Tao

In this paper, we propose a unified information theoretic framework for learning-motivated methods aimed at odometry estimation, a crucial component of many robotics and vision tas…