2025
Unraveling the Effects of Synthetic Data on End-to-End Autonomous Driving
ICCV 2025poster
End-to-end (E2E) autonomous driving (AD) models require diverse, high-quality data to perform well across various driving scenarios. However, collecting large-scale real-world data is expensive and time-consuming, making high-fidelity synthetic data essential for enhancing data diversity and model r…