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Found 5 papers, 1 papers with code
Rethinking Imitation-based Planner for Autonomous Driving
In recent years, imitation-based driving planners have reported considerable success.
Forecast-MAE: Self-supervised Pre-training for Motion Forecasting with Masked Autoencoders
This study explores the application of self-supervised learning (SSL) to the task of motion forecasting, an area that has not yet been extensively investigated despite the widespread success of SSL in computer vision and natural language processing.
Autonomous Navigation through intersections with Graph ConvolutionalNetworks and Conditional Imitation Learning for Self-driving Cars
To provide a solution to this problem, we propose a novel branched network G-CIL for the navigation policy learning.
HGCN-GJS: Hierarchical Graph Convolutional Network with Groupwise Joint Sampling for Trajectory Prediction
Fully investigating the social interactions within the crowd is crucial for accurate pedestrian trajectory prediction.
High-speed Autonomous Drifting with Deep Reinforcement Learning
Drifting is a complicated task for autonomous vehicle control.
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