no code implementations • 23 Jul 2020 • Shivam Akhauri, Laura Zheng, Ming Lin
Simulation data can be utilized to extend real-world driving data in order to cover edge cases, such as vehicle accidents.
no code implementations • 26 Feb 2021 • Yu Shen, Laura Zheng, Manli Shu, Weizi Li, Tom Goldstein, Ming C. Lin
For safety of autonomous driving, vehicles need to be able to drive under various lighting, weather, and visibility conditions in different environments.
no code implementations • 15 Mar 2021 • Shivam Akhauri, Laura Zheng, Tom Goldstein, Ming Lin
Practical learning-based autonomous driving models must be capable of generalizing learned behaviors from simulated to real domains, and from training data to unseen domains with unusual image properties.
no code implementations • NeurIPS 2021 • Yu Shen, Laura Zheng, Manli Shu, Weizi Li, Tom Goldstein, Ming Lin
We introduce a simple yet effective framework for improving the robustness of learning algorithms against image corruptions for autonomous driving.