SAM-Enhanced Segmentation on Road Datasets: Balancing Critical Classes in Autonomous Driving 事件

SAM-Enhanced Segmentation on Road Datasets: Balancing Critical Classes in Autonomous Driving arXiv:2605.28136v1 Announce Type: new Abstract: Dense semantic segmentation is essential for autonomous driving, yet many multi-modal datasets lack pixel-level annotations. The Zenseact Open Dataset (ZOD) provides rich multi-sensor data but only bounding-box labels, limiting its use for segmentation research. Our primary contribution is a Segment Anything Model (SAM)-based annotation pipeline that produ