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cs.CV2026

LoDA: A Level of Detection Aware Method and a Multimodal Sensing Benchmark for Object Level Change Detection

Haitian Wang, Xinyu Wang, Sheldon Fung +2

High-definition 3D LiDAR maps are important for autonomous driving and smart-city services, which require reliable detection of object-level changes in multi-temporal urban LiDAR t…

cs.CV2026

Edge-Efficient Two-Stream Multimodal Architecture for Non-Intrusive Bathroom Fall Detection

Haitian Wang, Yiren Wang, Xinyu Wang +2

Falls in wet bathroom environments are a major safety risk for seniors living alone. Recent work has shown that mmWave-only, vibration-only, and existing multimodal schemes, such a…

cs.CV2026

LiDAR-based 3D Change Detection at City Scale

Hezam Albagami, Hezam Albaqami, Haitian Wang +7

High-definition 3D city maps enable city planning and change detection, which is essential for municipal compliance, map maintenance, and asset monitoring, including both built str…

cs.CV2026

Geo-Registration of Terrestrial LiDAR Point Clouds with Satellite Images without GNSS

Xinyu Wang, Muhammad Ibrahim, Haitian Wang +3

Accurate geo-registration of LiDAR point clouds remains a significant challenge in urban environments where Global Navigation Satellite System (GNSS) signals are denied or degraded…

cs.CV2026

CymbaDiff: Structured Spatial Diffusion for Sketch-based 3D Semantic Urban Scene Generation

Li Liang, Bo Miao, Xinyu Wang +3

Outdoor 3D semantic scene generation produces realistic and semantically rich environments for applications such as urban simulation and autonomous driving. However, advances in th…

cs.CV2025

P2MFDS: A Privacy-Preserving Multimodal Fall Detection System for Elderly People in Bathroom Environments

Haitian Wang, Yiren Wang, Xinyu Wang +4

By 2050, people aged 65 and over are projected to make up 16% of the global population. As aging is closely associated with increased fall risk, particularly in wet and confined en…