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Found 3 papers, 3 papers with code
Efficient Baselines for Motion Prediction in Autonomous Driving
However, despite many approaches use simple ConvNets and LSTMs to obtain the social latent features, State-Of-The-Art (SOTA) models might be too complex for real-time applications when using both sources of information (map and past trajectories) as well as little interpretable, specially considering the physical information.
Exploring Attention GAN for Vehicle Motion Prediction
The design of a safe and reliable Autonomous Driving stack (ADS) is one of the most challenging tasks of our era.
Exploring Map-based Features for Efficient Attention-based Vehicle Motion Prediction
Motion prediction (MP) of multiple agents is a crucial task in arbitrarily complex environments, from social robots to self-driving cars.
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