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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

BAWSeg: A UAV Multispectral Benchmark for Barley Weed Segmentation

Haitian Wang, Xinyu Wang, Muhammad Ibrahim +2

Accurate weed mapping in cereal fields requires pixel-level segmentation from UAV imagery that remains reliable across fields, seasons, and illumination. Existing multispectral pip…

cs.CV2025

Multistream Network for LiDAR and Camera-based 3D Object Detection in Outdoor Scenes

Muhammad Ibrahim, Naveed Akhtar, Haitian Wang +2

Fusion of LiDAR and RGB data has the potential to enhance outdoor 3D object detection accuracy. To address real-world challenges in outdoor 3D object detection, fusion of LiDAR and…

cs.CV2025

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.CV2025

Multispectral Remote Sensing for Weed Detection in West Australian Agricultural Lands

Haitian Wang, Muhammad Ibrahim, Yumeng Miao +3

The Kondinin region in Western Australia faces significant agricultural challenges due to pervasive weed infestations, causing economic losses and ecological impacts. This study co…