CIRL: Controllable Imitative Reinforcement Learning for Vision-based Self-driving

no code implementations • ECCV 2018 • Xiaodan Liang, Tairui Wang, Luona Yang, Eric Xing

To our knowledge, this is the first successful case of the learned driving policy through reinforcement learning in the high-fidelity simulator, which performs better-than supervised imitation learning.

Imitation Learning reinforcement-learning +1

Real-to-Virtual Domain Unification for End-to-End Autonomous Driving

no code implementations • ECCV 2018 • Luona Yang, Xiaodan Liang, Tairui Wang, Eric Xing

In the spectrum of vision-based autonomous driving, vanilla end-to-end models are not interpretable and suboptimal in performance, while mediated perception models require additional intermediate representations such as segmentation masks or detection bounding boxes, whose annotation can be prohibitively expensive as we move to a larger scale.

Autonomous Driving