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Found 3 papers, 2 papers with code
PathGAN: Local Path Planning with Attentive Generative Adversarial Networks
To achieve autonomous driving without high-definition maps, we present a model capable of generating multiple plausible paths from egocentric images for autonomous vehicles.
Regularizing Neural Networks for Future Trajectory Prediction via Inverse Reinforcement Learning Framework
We train the networks of the proposed model to produce a future trajectory, which is the closest to the true trajectory, while maximizing a reward from a reward function.
Driving Experience Transfer Method for End-to-End Control of Self-Driving Cars
In this paper, we present a transfer learning method for the end-to-end control of self-driving cars, which enables a convolutional neural network (CNN) trained on a source domain to be utilized for the same task in a different target domain.
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