5 papers
WHU-Infra3D: A Full-stack Multi-modal Dataset and Benchmark for 3D Roadside Infrastructure Inventory
Chong Liu, Luxuan Fu, Xuyu Feng +2
The paradigm of digital twin cities is shifting from coarse visual mapping toward more precise and actionable digitization of urban assets. However, existing datasets predominantly…
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…
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…
Empowering Bridge Digital Twins by Bridging the Data Gap with a Unified Synthesis Framework
Wang Wang, Mingyu Shi, Jun Jiang +4
As critical transportation infrastructure, bridges face escalating challenges from aging and deterioration, while traditional manual inspection methods suffer from low efficiency.…
ME-CPT: Multi-Task Enhanced Cross-Temporal Point Transformer for Urban 3D Change Detection
Luqi Zhang, Haiping Wang, Chong Liu +2
The point clouds collected by the Airborne Laser Scanning (ALS) system provide accurate 3D information of urban land covers. By utilizing multi-temporal ALS point clouds, semantic…