collaborators

6 papers

cs.CV2026

SpatiaLoc: Leveraging Multi-Level Spatial Enhanced Descriptors for Cross-Modal Localization

Tianyi Shang, Pengjie Xu, Zhaojun Deng +3

Cross-modal localization using text and point clouds enables robots to localize themselves via natural language descriptions, with applications in autonomous navigation and interac…

cs.CV2025

Vehicle-Scene Interaction: A Text-Driven 3D Lidar Place Recognition Method for Autonomous Driving

Tianyi Shang, Zhenyu Li, Pengjie Xu +1

Environment description-based localization in large-scale point cloud maps constructed through remote sensing is critically significant for the advancement of large-scale autonomou…

cs.CV2025

OptiCorNet: Optimizing Sequence-Based Context Correlation for Visual Place Recognition

Zhenyu Li, Tianyi Shang, Pengjie Xu +2

Visual Place Recognition (VPR) in dynamic and perceptually aliased environments remains a fundamental challenge for long-term localization. Existing deep learning-based solutions p…

cs.CV2025

Place Recognition Meet Multiple Modalitie: A Comprehensive Review, Current Challenges and Future Directions

Zhenyu Li, Tianyi Shang, Pengjie Xu +1

Place recognition is a cornerstone of vehicle navigation and mapping, which is pivotal in enabling systems to determine whether a location has been previously visited. This capabil…

cs.CV2025

Bridging Text and Vision: A Multi-View Text-Vision Registration Approach for Cross-Modal Place Recognition

Tianyi Shang, Zhenyu Li, Pengjie Xu +4

Mobile robots necessitate advanced natural language understanding capabilities to accurately identify locations and perform tasks such as package delivery. However, traditional vis…

cs.CV2025

MambaPlace:Text-to-Point-Cloud Cross-Modal Place Recognition with Attention Mamba Mechanisms

Tianyi Shang, Zhenyu Li, Pengjie Xu +1

Vision Language Place Recognition (VLVPR) enhances robot localization performance by incorporating natural language descriptions from images. By utilizing language information, VLV…