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Safety hazard identification and prevention are the key elements of proactive safety management. Previous research has extensively explored the applications of computer vision to automatically identify hazards from image clips collected…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Muhammad Adil , Gaang Lee , Vicente A. Gonzalez , Qipei Mei

Construction safety inspection remains mostly manual, and automated approaches still rely on task-specific datasets that are hard to maintain in fast-changing construction environments due to frequent retraining. Meanwhile, field inspection…

Robotics · Computer Science 2025-12-17 Hossein Naderi , Alireza Shojaei , Philip Agee , Kereshmeh Afsari , Abiola Akanmu

Large-scale Vision Language Models (LVLMs) exhibit advanced capabilities in tasks that require visual information, including object detection. These capabilities have promising applications in various industrial domains, such as autonomous…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Haruki Sakajo , Hiroshi Takato , Hiroshi Tsutsui , Komei Soda , Hidetaka Kamigaito , Taro Watanabe

We propose general visual inspection model using Vision-Language Model~(VLM) with few-shot images of non-defective or defective products, along with explanatory texts that serve as inspection criteria. Although existing VLM exhibit high…

Computer Vision and Pattern Recognition · Computer Science 2025-02-14 Shiryu Ueno , Yoshikazu Hayashi , Shunsuke Nakatsuka , Yusei Yamada , Hiroaki Aizawa , Kunihito Kato

Laboratories are prone to severe injuries from minor unsafe actions, yet continuous safety monitoring -- beyond mandatory pre-lab safety training -- is limited by human availability. Vision language models (VLMs) offer promise for…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 Trishna Chakraborty , Udita Ghosh , Aldair Ernesto Gongora , Ruben Glatt , Yue Dong , Jiachen Li , Amit K. Roy-Chowdhury , Chengyu Song

Industrial accidents, particularly in high-risk domains such as surface and underground mining, are frequently caused by unsafe worker behaviors. Traditional manual inspection remains labor-intensive, error-prone, and insufficient for…

Computer Vision and Pattern Recognition · Computer Science 2026-03-12 Jiang Wu , Sichao Wu , Yinsong Ma , Guangyuan Yu , Haoyuan Xu , Lifang Zheng , Jingliang Duan

This thesis explores a multimodal AI framework for enhancing construction safety through the combined analysis of textual and visual data. In safety-critical environments such as construction sites, accident data often exists in multiple…

Artificial Intelligence · Computer Science 2025-11-21 Islem Sahraoui

The widespread use of cameras in our society has created an overwhelming amount of video data, far exceeding the capacity for human monitoring. This presents a critical challenge for public safety and security, as the timely detection of…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Pascal Benschop , Cristian Meo , Justin Dauwels , Jelte P. Mense

Accurate and timely identification of construction hazards around workers is essential for preventing workplace accidents. While large vision-language models (VLMs) demonstrate strong contextual reasoning capabilities, their high…

Computer Vision and Pattern Recognition · Computer Science 2026-04-08 Muhammad Adil , Mehmood Ahmed , Muhammad Aqib , Vicente A. Gonzalez , Gaang Lee , Qipei Mei

This paper evaluates the use of vision-language models (VLMs) for zero-shot detection and association of hardhats to enhance construction safety. Given the significant risk of head injuries in construction, proper enforcement of hardhat use…

Computer Vision and Pattern Recognition · Computer Science 2024-10-17 Lucas Choi , Ross Greer

As robotics become increasingly integrated into construction workflows, their ability to interpret and respond to human behavior will be essential for enabling safe and effective collaboration. Vision-Language Models (VLMs) have emerged as…

Computer Vision and Pattern Recognition · Computer Science 2026-01-19 Hieu Bui , Nathaniel E. Chodosh , Arash Tavakoli

Most visual recognition studies rely heavily on crowd-labelled data in deep neural networks (DNNs) training, and they usually train a DNN for each single visual recognition task, leading to a laborious and time-consuming visual recognition…

Computer Vision and Pattern Recognition · Computer Science 2024-02-19 Jingyi Zhang , Jiaxing Huang , Sheng Jin , Shijian Lu

Current vision large language models (VLLMs) exhibit remarkable capabilities yet are prone to generate harmful content and are vulnerable to even the simplest jailbreaking attacks. Our initial analysis finds that this is due to the presence…

Machine Learning · Computer Science 2024-06-19 Yongshuo Zong , Ondrej Bohdal , Tingyang Yu , Yongxin Yang , Timothy Hospedales

Benefiting from the powerful capabilities of Large Language Models (LLMs), pre-trained visual encoder models connected to an LLMs can realize Vision Language Models (VLMs). However, existing research shows that the visual modality of VLMs…

Computer Vision and Pattern Recognition · Computer Science 2024-05-24 Zhendong Liu , Yuanbi Nie , Yingshui Tan , Xiangyu Yue , Qiushi Cui , Chongjun Wang , Xiaoyong Zhu , Bo Zheng

Urban monitoring of public infrastructure (such as waste bins, road signs, vegetation, sidewalks, and construction sites) poses significant challenges due to the diversity of objects, environments, and contextual conditions involved.…

Computer Vision and Pattern Recognition · Computer Science 2025-10-15 André Torneiro , Diogo Monteiro , Paulo Novais , Pedro Rangel Henriques , Nuno F. Rodrigues

Vision-Language Model (VLM) have gained widespread adoption in Open-Vocabulary (OV) object detection and segmentation tasks. Despite they have shown promise on OV-related tasks, their effectiveness in conventional vision tasks has thus far…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Yongchao Feng , Yajie Liu , Shuai Yang , Wenrui Cai , Jinqing Zhang , Qiqi Zhan , Ziyue Huang , Hongxi Yan , Qiao Wan , Chenguang Liu , Junzhe Wang , Jiahui Lv , Ziqi Liu , Tengyuan Shi , Qingjie Liu , Yunhong Wang

Recent developments in vision language models (VLM) have shown great potential for diverse applications related to image understanding. In this study, we have explored state-of-the-art VLM models for vision-based transportation engineering…

Computer Vision and Pattern Recognition · Computer Science 2024-09-05 Sanjita Prajapati , Tanu Singh , Chinmay Hegde , Pranamesh Chakraborty

Vision-Language Models (VLMs) trained on web-scale corpora excel at natural image tasks and are increasingly repurposed for healthcare; however, their competence in medical tasks remains underexplored. We present a comprehensive evaluation…

Computer Vision and Pattern Recognition · Computer Science 2025-07-21 Che Liu , Jiazhen Pan , Weixiang Shen , Wenjia Bai , Daniel Rueckert , Rossella Arcucci

Conventional construction safety inspection methods are often inefficient as they require navigating through large volume of information. Recent advances in large vision-language models (LVLMs) provide opportunities to automate safety…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Chenxin Wang , Elyas Asadi Shamsabadi , Zhaohui Chen , Luming Shen , Alireza Ahmadian Fard Fini , Daniel Dias-da-Costa

Vision Large Language Models (VLLMs) have demonstrated impressive capabilities in general visual tasks such as image captioning and visual question answering. However, their effectiveness in specialized, safety-critical domains like…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Tong Zeng , Longfeng Wu , Liang Shi , Dawei Zhou , Feng Guo
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