5 papers
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…
A2GC: Asymmetric Aggregation with Geometric Constraints for Locally Aggregated Descriptors
Zhenyu Li, Tianyi Shang
Visual Place Recognition (VPR) aims to match query images against a database using visual cues. State-of-the-art methods aggregate features from deep backbones to form global descr…
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…
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…
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…