activity
20242026
collaborators

8 papers

cs.CV2026

Unleashing the Capabilities of Large Vision-Language Models for Intelligent Perception of Roadside Infrastructure

Luxuan Fu, Chong Liu, Bisheng Yang +1

Automated perception of urban roadside infrastructure is crucial for smart city management, yet general-purpose models often struggle to capture the necessary fine-grained attribut…

cs.CV2026

SVII-3D: Advancing Roadside Infrastructure Inventory with Decimeter-level 3D Localization and Comprehension from Sparse Street Imagery

Chong Liu, Luxuan Fu, Yang Jia +2

The automated creation of digital twins and precise asset inventories is a critical task in smart city construction and facility lifecycle management. However, utilizing cost-effec…

cs.RO2025

Aerial-ground Cross-modal Localization: Dataset, Ground-truth, and Benchmark

Yandi Yang, Jianping Li, Youqi Liao +5

Accurate visual localization in dense urban environments poses a fundamental task in photogrammetry, geospatial information science, and robotics. While imagery is a low-cost and w…

cs.CV2025

LifelongPR: Lifelong point cloud place recognition based on sample replay and prompt learning

Xianghong Zou, Jianping Li, Zhe Chen +4

Point cloud place recognition (PCPR) determines the geo-location within a prebuilt map and plays a crucial role in geoscience and robotics applications such as autonomous driving,…

cs.RO2025

ARMOR: Adaptive Meshing with Reinforcement Optimization for Real-time 3D Monitoring in Unexposed Scenes

Yizhe Zhang, Jianping Li, Xin Zhao +3

Unexposed environments, such as lava tubes, mines, and tunnels, are among the most complex yet strategically significant domains for scientific exploration and infrastructure devel…

cs.CV2024

SaliencyI2PLoc: saliency-guided image-point cloud localization using contrastive learning

Yuhao Li, Jianping Li, Zhen Dong +2

Image to point cloud global localization is crucial for robot navigation in GNSS-denied environments and has become increasingly important for multi-robot map fusion and urban asse…