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Found 3 papers, 2 papers with code
Exploring Navigation Maps for Learning-Based Motion Prediction
Combined with our method for knowledge distillation, we achieve results that are close to the original HD map-reliant models.
CRAT-Pred: Vehicle Trajectory Prediction with Crystal Graph Convolutional Neural Networks and Multi-Head Self-Attention
We therefore propose CRAT-Pred, a multi-modal and non-rasterization-based trajectory prediction model, specifically designed to effectively model social interactions between vehicles, without relying on map information.
Ranked #174 on
Motion Forecasting
on Argoverse CVPR 2020
Rapid Exact Signal Scanning with Deep Convolutional Neural Networks
A rigorous formulation of the dynamics of a signal processing scheme aimed at dense signal scanning without any loss in accuracy is introduced and analyzed.
