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Longteng Fan

1 accepted papers

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…