Automotive datasets fuel advances in autonomous driving and computer vision, offering rich, sensor-rich inputs for training and evaluation. Notable collections include KITTI, Cityscapes, ApolloScape, and BDD100K, featuring imagery, segmentation, and depth data. Multimodal datasets like nuScenes and A2D2 provide synchronized camera, LiDAR, radar, and GPS data for robust detection and perception .Argoverse adds motion forecasting and HD map overlays for improved trajectory modeling. Recent innovations include WayveScenes101 (novel view synthesis), DurLAR’s fine-grained 128-channel LiDAR, and synthetic event-based vision datasets like SEVD. Together, these datasets drive precision, safety, and scalability in automotive AI.