2024
DriveSceneGen: Generating Diverse and Realistic Driving Scenarios From Scratch
RA-L 2024
Realistic and diverse traffic scenarios in large quantities are crucial for the development and validation of autonomous driving systems. However, owing to numerous difficulties in the data collection process and the reliance on intensive annotations, real-world datasets lack sufficient quantity and