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Attentional Bottleneck: Towards an Interpretable Deep Driving Network
Deep neural networks are a key component of behavior prediction and moti...
05/08/2020 ∙ by Jinkyu Kim, et al. ∙
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MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction
Predicting human behavior is a difficult and crucial task required for m...
10/12/2019 ∙ by Yuning Chai, et al. ∙
12
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ChauffeurNet: Learning to Drive by Imitating the Best and Synthesizing the Worst
Our goal is to train a policy for autonomous driving via imitation learn...
12/07/2018 ∙ by Mayank Bansal, et al. ∙
10
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Geometric Polynomial Constraints in Higher-Order Graph Matching
Correspondence is a ubiquitous problem in computer vision and graph matc...
05/24/2014 ∙ by Mayank Bansal, et al. ∙
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