activity
20212025
most citedNeMO: Neural Map Growing System for Spatiotemporal Fusion in Bird's-Eye-View and BDD-Map Benchmark

3 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

eess.SP2025

Towards personalized, precise and survey-free environment recognition: AI-enhanced sensor fusion without pre-deployment

Ruichen Wang, Zhikang Ni, Pengzhou Wang +3

Accurate and personalized environment recognition is essential for seamless indoor positioning and optimized connectivity, yet traditional fingerprinting requires costly site surve…

cs.CV2024

BezierFormer: A Unified Architecture for 2D and 3D Lane Detection

Zhiwei Dong, Xi Zhu, Xiya Cao +5

Lane detection has made significant progress in recent years, but there is not a unified architecture for its two sub-tasks: 2D lane detection and 3D lane detection. To fill this g…

cs.RO2023★ 1 cited

A survey on deep learning approaches for data integration in autonomous driving system

Xi Zhu, Likang Wang, Caifa Zhou +3

The perception module of self-driving vehicles relies on a multi-sensor system to understand its environment. Recent advancements in deep learning have led to the rapid development…

cs.CV2023★ 3 cited

NeMO: Neural Map Growing System for Spatiotemporal Fusion in Bird's-Eye-View and BDD-Map Benchmark

Xi Zhu, Xiya Cao, Zhiwei Dong +4

Vision-centric Bird's-Eye View (BEV) representation is essential for autonomous driving systems (ADS). Multi-frame temporal fusion which leverages historical information has been d…

stat.ML2021

RIO: Rotation-equivariance supervised learning of robust inertial odometry

Caifa Zhou, Xiya Cao, Dandan Zeng +1

This paper introduces rotation-equivariance as a self-supervisor to train inertial odometry models. We demonstrate that the self-supervised scheme provides a powerful supervisory s…