4 citations · 5 across the 4 of their papers we have counts for
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cs.RO2024
Learning to Drive via Asymmetric Self-Play
Chris Zhang, Sourav Biswas, Kelvin Wong +5
Large-scale data is crucial for learning realistic and capable driving policies. However, it can be impractical to rely on scaling datasets with real data alone. The majority of dr…
cs.RO2019★ 4 cited
Learning by Cheating
Dian Chen, Brady Zhou, Vladlen Koltun +1
Vision-based urban driving is hard. The autonomous system needs to learn to perceive the world and act in it. We show that this challenging learning problem can be simplified by de…