137 citations · 138 across the 2 of their papers we have counts for
3 papers
cs.CV2020★ 1 cited
Attentional Bottleneck: Towards an Interpretable Deep Driving Network
Jinkyu Kim, Mayank Bansal
Deep neural networks are a key component of behavior prediction and motion generation for self-driving cars. One of their main drawbacks is a lack of transparency: they should prov…
cs.LG2019★ 137 cited
MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction
Yuning Chai, Benjamin Sapp, Mayank Bansal +1
Predicting human behavior is a difficult and crucial task required for motion planning. It is challenging in large part due to the highly uncertain and multi-modal set of possible…
cs.RO2018
ChauffeurNet: Learning to Drive by Imitating the Best and Synthesizing the Worst
Mayank Bansal, Alex Krizhevsky, Abhijit Ogale
Our goal is to train a policy for autonomous driving via imitation learning that is robust enough to drive a real vehicle. We find that standard behavior cloning is insufficient fo…