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20232025
most citedVCVW-3D: A Virtual Construction Vehicles and Workers Dataset with 3D Annotations

16 citations · 22 across the 7 of their papers we have counts for

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6 papers · 1 filter

cs.CV2024

Scan-to-BIM for As-built Roads: Automatic Road Digital Twinning from Semantically Labeled Point Cloud Data

Yuexiong Ding, Mengtian Yin, Ran Wei +3

Creating geometric digital twins (gDT) for as-built roads still faces many challenges, such as low automation level and accuracy, limited asset types and shapes, and reliance on en…

cs.CV2024★ 2 cited

SDNIA-YOLO: A Robust Object Detection Model for Extreme Weather Conditions

Yuexiong Ding, Xiaowei Luo

Though current object detection models based on deep learning have achieved excellent results on many conventional benchmark datasets, their performance will dramatically decline o…

cs.CV2023

Personal Protective Equipment Detection in Extreme Construction Conditions

Yuexiong Ding, Xiaowei Luo

Object detection has been widely applied for construction safety management, especially personal protective equipment (PPE) detection. Though the existing PPE detection models trai…

cs.CV2023★ 1 cited

Scene restoration from scaffold occlusion using deep learning-based methods

Yuexiong Ding, Muyang Liu, Xiaowei Luo

The occlusion issues of computer vision (CV) applications in construction have attracted significant attention, especially those caused by the wide-coverage, crisscrossed, and immo…

cs.CV2023★ 16 cited

VCVW-3D: A Virtual Construction Vehicles and Workers Dataset with 3D Annotations

Yuexiong Ding, Xiaowei Luo

Currently, object detection applications in construction are almost based on pure 2D data (both image and annotation are 2D-based), resulting in the developed artificial intelligen…

cs.CV2023★ 3 cited

Monocular 2D Camera-based Proximity Monitoring for Human-Machine Collision Warning on Construction Sites

Yuexiong Ding, Xiaowei Luo

Accident of struck-by machines is one of the leading causes of casualties on construction sites. Monitoring workers' proximities to avoid human-machine collisions has aroused great…