{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:02:41Z","timestamp":1760058161892,"version":"build-2065373602"},"reference-count":28,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2025,3,14]],"date-time":"2025-03-14T00:00:00Z","timestamp":1741910400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Information Society Agency (NIA) of the Republic of Korea"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Data"],"abstract":"<jats:p>Comprehensive datasets are crucial for developing advanced AI solutions in road infrastructure, yet most existing resources focus narrowly on vehicles or a limited set of object categories. To address this gap, we introduce the Korean Road Infrastructure Dataset (KRID), a large-scale dataset designed for real-world road maintenance and safety applications. Our dataset covers highways, national roads, and local roads in both city and non-city areas, comprising 34 distinct types of road infrastructure\u2014from common elements (e.g., traffic signals, gaze-directed poles) to specialized structures (e.g., tunnels, guardrails). Each instance is annotated with either bounding boxes or polygon segmentation masks under stringent quality control and privacy protocols. To demonstrate the utility of this resource, we conducted object detection and segmentation experiments using YOLO-based models, focusing on guardrail damage detection and traffic sign recognition. Preliminary results confirm its suitability for complex, safety-critical scenarios in intelligent transportation systems. Our main contributions include: (1) a broader range of infrastructure classes than conventional \u201cdriving perception\u201d datasets, (2) high-resolution, privacy-compliant annotations across diverse road conditions, and (3) open-access availability through AI Hub and GitHub. By highlighting critical yet often overlooked infrastructure elements, this dataset paves the way for AI-driven maintenance workflows, hazard detection, and further innovations in road safety.<\/jats:p>","DOI":"10.3390\/data10030036","type":"journal-article","created":{"date-parts":[[2025,3,14]],"date-time":"2025-03-14T08:46:46Z","timestamp":1741942006000},"page":"36","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["KRID: A Large-Scale Nationwide Korean Road Infrastructure Dataset for Comprehensive Road Facility Recognition"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2264-9962","authenticated-orcid":false,"given":"Hyeongbok","family":"Kim","sequence":"first","affiliation":[{"name":"Testworks, Inc., Seoul 01000, Republic of Korea"},{"name":"Faculty of Computing, Harbin Institute of Technology, Harbin 150001, China"}]},{"given":"Eunbi","family":"Kim","sequence":"additional","affiliation":[{"name":"Testworks, Inc., Seoul 01000, Republic of Korea"}]},{"given":"Sanghoon","family":"Ahn","sequence":"additional","affiliation":[{"name":"Testworks, Inc., Seoul 01000, Republic of Korea"}]},{"given":"Beomjin","family":"Kim","sequence":"additional","affiliation":[{"name":"Testworks, Inc., Seoul 01000, Republic of Korea"}]},{"given":"Sung Jin","family":"Kim","sequence":"additional","affiliation":[{"name":"Korea Automotive Technology Institute (KATECH), Cheonan-si 31000, Republic of Korea"}]},{"given":"Tae Kyung","family":"Sung","sequence":"additional","affiliation":[{"name":"WiFive Ltd., Daejeon 34000, Republic of Korea"}]},{"given":"Lingling","family":"Zhao","sequence":"additional","affiliation":[{"name":"Faculty of Computing, Harbin Institute of Technology, Harbin 150001, China"}]},{"given":"Xiaohong","family":"Su","sequence":"additional","affiliation":[{"name":"Faculty of Computing, Harbin Institute of Technology, Harbin 150001, China"}]},{"given":"Gilmu","family":"Dong","sequence":"additional","affiliation":[{"name":"Testworks, Inc., Seoul 01000, Republic of Korea"}]}],"member":"1968","published-online":{"date-parts":[[2025,3,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Deng, J., Dong, W., Socher, R., Li, L.J., Li, K., and Li, F.-F. 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