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Found 4 papers, 2 papers with code
Conditional Unscented Autoencoders for Trajectory Prediction
We leverage recent advances in the space of the VAE, the foundation of the CVAE, which show that a simple change in the sampling procedure can greatly benefit performance.
Unscented Autoencoder
The Variational Autoencoder (VAE) is a seminal approach in deep generative modeling with latent variables.
Bridging the Gap Between Multi-Step and One-Shot Trajectory Prediction via Self-Supervision
Accurate vehicle trajectory prediction is an unsolved problem in autonomous driving with various open research questions.
Self-Supervised Action-Space Prediction for Automated Driving
In this paper, we present a novel learned multi-modal trajectory prediction architecture for automated driving.
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