Behavioral intention prediction in driving scenes: A survey
In driving scenes, road agents often engage in frequent interaction and strive to understand
their surroundings. Ego-agent (each road agent itself) predicts what behavior will be …
their surroundings. Ego-agent (each road agent itself) predicts what behavior will be …
Gohome: Graph-oriented heatmap output for future motion estimation
In this paper, we propose GOHOME, a method leveraging graph representations of the High
Definition Map and sparse projections to generate a heatmap output representing the future …
Definition Map and sparse projections to generate a heatmap output representing the future …
Vip3d: End-to-end visual trajectory prediction via 3d agent queries
Perception and prediction are two separate modules in the existing autonomous driving
systems. They interact with each other via hand-picked features such as agent bounding …
systems. They interact with each other via hand-picked features such as agent bounding …
On adversarial robustness of trajectory prediction for autonomous vehicles
Trajectory prediction is a critical component for autonomous vehicles (AVs) to perform safe
planning and navigation. However, few studies have analyzed the adversarial robustness of …
planning and navigation. However, few studies have analyzed the adversarial robustness of …
Human action recognition and prediction: A survey
Derived from rapid advances in computer vision and machine learning, video analysis tasks
have been moving from inferring the present state to predicting the future state. Vision-based …
have been moving from inferring the present state to predicting the future state. Vision-based …
Rethinking integration of prediction and planning in deep learning-based automated driving systems: a review
Automated driving has the potential to revolutionize personal, public, and freight mobility.
Besides the enormous challenge of perception, ie accurately perceiving the environment …
Besides the enormous challenge of perception, ie accurately perceiving the environment …
Thomas: Trajectory heatmap output with learned multi-agent sampling
In this paper, we propose THOMAS, a joint multi-agent trajectory prediction framework
allowing for an efficient and consistent prediction of multi-agent multi-modal trajectories. We …
allowing for an efficient and consistent prediction of multi-agent multi-modal trajectories. We …
BEV-V2X: Cooperative birds-eye-view fusion and grid occupancy prediction via V2X-based data sharing
Birds-Eye-View (BEV) perception can naturally represent natural scenes, which is conducive
to multimodal data processing and fusion. BEV data contain rich semantics and integrate the …
to multimodal data processing and fusion. BEV data contain rich semantics and integrate the …
Laformer: Trajectory prediction for autonomous driving with lane-aware scene constraints
Existing trajectory prediction methods for autonomous driving typically rely on one-stage
trajectory prediction models which condition future trajectories on observed trajectories …
trajectory prediction models which condition future trajectories on observed trajectories …
A survey on deep-learning approaches for vehicle trajectory prediction in autonomous driving
With the rapid development of machine learning, autonomous driving has become a hot
issue, making urgent demands for more intelligent perception and planning systems. Self …
issue, making urgent demands for more intelligent perception and planning systems. Self …