Transport & Automotive

This dataset focuses on license plate recognition and vehicle attribute analysis in underground parking lots, supporting object detection tasks.

This dataset provides a large collection of video data on illegal parking causing traffic blockages, aiming to enhance the intelligence of traffic management systems.

This dataset focuses on motorcycle traffic accident risk analysis, providing high-quality image data and detailed annotations.

This dataset focuses on illegal parking detection on urban roads, providing abundant labeled images and detailed information.

This dataset focuses on the operational safety monitoring of train carriages, aiming to enhance the efficiency and accuracy of object detection technology applications in the transportation industry.

This dataset focuses on identifying traffic violations by motorcycles and electric vehicles, aiding the development of intelligent transportation systems.

This dataset is used to detect stall and obstruction behaviors within transportation hub stations to improve traffic management efficiency.

This dataset focuses on the automatic recognition of tunnel traffic control signs, promoting the process of traffic intelligence.

This dataset focuses on motorcycle travel and license plate recognition, aiding the research and application of intelligent transportation systems.

The Underground Parking Lot Empty Slot Detection Dataset aids efficient parking management.

This dataset provides high-quality images for vehicle collision accidents, supporting research on target detection and damage assessment.

This dataset provides classification images of various congested scenes at highway entrances, aiming to enhance the automatic recognition capabilities of intelligent traffic systems.

This dataset focuses on image classification of high-speed rear-end collision risk scenarios, aiming to enhance traffic safety management capabilities.

This dataset focuses on semantic segmentation of vehicle collision damage in tunnel environments, aiming to improve the efficiency and accuracy of traffic accident analysis.

This dataset focuses on identifying stall and occupancy behaviors at transportation hubs to support urban management.

This dataset focuses on the detection of severe highway accidents to aid the development of intelligent transportation systems.

This dataset is used for the lane segmentation task in autonomous driving systems to improve driving safety and accuracy.

This is a dataset focused on in-car driving perspective target detection under rainy conditions.

This dataset focuses on the damage segmentation of high-speed rear-end vehicles, providing high-quality images and detailed annotation information.

Driver simulated driving control posture image dataset for analyzing and enhancing control posture recognition in traffic driving.