{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T13:01:10Z","timestamp":1785416470163,"version":"3.56.0"},"reference-count":45,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T00:00:00Z","timestamp":1775865600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100011878","name":"Flemish Government","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100011878","id-type":"DOI","asserted-by":"crossref"}]},{"id":[{"id":"https:\/\/ror.org\/04qxsrb28","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>As autonomous driving technology advances, the deployment of autonomous vehicles in urban environments is rapidly increasing. Lens flare\u2014an often overlooked optical artifact in object detection research\u2014can lead to increased false positives or missed detections, particularly in the challenging conditions inherent to autonomous driving. Current mitigation methods are often ill-suited for real-time implementation. This work proposes a solution to alleviate the adverse effects of lens flare by utilizing a lightweight lens flare perception network, eliminating the need for additional hardware or complex image pre-processing. Specifically, we propose a reference-free model utilizing a ResNet18 backbone integrated with a lightweight Multi-Layer Perceptron (MLP) to extract and leverage lens flare information. This model is developed via a teacher\u2013student framework, which was distilled from an end-to-end reference-based model optimized using the Learned Perceptual Image Patch Similarity (LPIPS) metric. Our experiments demonstrate that incorporating lens flare information significantly enhances the performance of the baseline object detection network, outperforming previous mitigation methods by a substantial margin. The proposed method can be seamlessly integrated into existing object detectors and requires only an efficient training process, facilitating its deployment in practical autonomous driving tasks.<\/jats:p>","DOI":"10.3390\/s26082359","type":"journal-article","created":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T07:29:29Z","timestamp":1776065369000},"page":"2359","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Reference-Free Lens-Flare-Aware Detector for Autonomous Driving"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5650-0168","authenticated-orcid":false,"given":"Shanxing","family":"Ma","sequence":"first","affiliation":[{"name":"Department of Telecommunications and Information Processing-Image Processing and Interpretation (TELIN-IPI), Ghent University\u2014imec, Sint-Pietersnieuwstraat 41, 9000 Ghent, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5264-919X","authenticated-orcid":false,"given":"Tim","family":"Willems","sequence":"additional","affiliation":[{"name":"Department of Telecommunications and Information Processing-Image Processing and Interpretation (TELIN-IPI), Ghent University\u2014imec, Sint-Pietersnieuwstraat 41, 9000 Ghent, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0144-3538","authenticated-orcid":false,"given":"Wenwen","family":"Ma","sequence":"additional","affiliation":[{"name":"Department of Telecommunications and Information Processing-Image Processing and Interpretation (TELIN-IPI), Ghent University\u2014imec, Sint-Pietersnieuwstraat 41, 9000 Ghent, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3350-6791","authenticated-orcid":false,"given":"Marwan","family":"Yusuf","sequence":"additional","affiliation":[{"name":"Department of Telecommunications and Information Processing-Image Processing and Interpretation (TELIN-IPI), Ghent University\u2014imec, Sint-Pietersnieuwstraat 41, 9000 Ghent, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2112-3475","authenticated-orcid":false,"given":"David Van","family":"Hamme","sequence":"additional","affiliation":[{"name":"Department of Telecommunications and Information Processing-Image Processing and Interpretation (TELIN-IPI), Ghent University\u2014imec, Sint-Pietersnieuwstraat 41, 9000 Ghent, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5543-2631","authenticated-orcid":false,"given":"Jan","family":"Aelterman","sequence":"additional","affiliation":[{"name":"Department of Telecommunications and Information Processing-Image Processing and Interpretation (TELIN-IPI), Ghent University\u2014imec, Sint-Pietersnieuwstraat 41, 9000 Ghent, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wilfried","family":"Philips","sequence":"additional","affiliation":[{"name":"Department of Telecommunications and Information Processing-Image Processing and Interpretation (TELIN-IPI), Ghent University\u2014imec, Sint-Pietersnieuwstraat 41, 9000 Ghent, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,4,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1016\/j.jth.2017.04.004","article-title":"Autonomous vehicles: Developing a public health research agenda to frame the future of transportation policy","volume":"6","author":"Crayton","year":"2017","journal-title":"J. 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