LCRM: A Linear-Camera Dataset for Road Marking Segmentation and Damage Evaluation

We introduce the Linear-Camera Road Marking (LCRM) dataset, which is the first to couple <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">segmentation</i> with <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">marking damage evaluation</i> on the same images, and the first captured with a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">linear (line-scan) camera</i>. LCRM spans Russian cities, covers 12 marking types, and grades instance damage with a 3-level scheme aligned with maintenance thresholds. We release 3,966 labeled images (train/test) and 18,847 unlabeled images. We also benchmark representative models across four tasks (binary and multi-class semantic segmentation, instance segmentation, and damage evaluation) to establish baselines for this new sensing regime.