Interactions between road agents present a significant challenge in
traj...
As learning-based methods make their way from perception systems to
plan...
Advancements in simulation and formal methods-guided environment samplin...
Game theoretic methods have become popular for planning and prediction i...
To construct effective teaming strategies between humans and AI systems ...
Multi-agent interactions are important to model for forecasting other ag...
We constantly integrate our knowledge and understanding of the world to
...
Language allows humans to build mental models that interpret what is
hap...
Motion prediction is important for intelligent driving systems, providin...
We propose a computational model to estimate a person's attended awarene...
Modeling multi-modal high-level intent is important for ensuring diversi...
Risk-bounded motion planning is an important yet difficult problem for
s...
Comprehension of surgical workflow is the foundation upon which computer...
Automated Vehicles require exhaustive testing in simulation to detect as...
Traffic simulators are important tools in autonomous driving development...
Reasoning about human motion is a core component of modern human-robot
i...
Analyzing surgical workflow is crucial for computers to understand surge...
Safe autonomous driving requires robust detection of other traffic
parti...
Autonomous driving has achieved significant progress in recent years, bu...
Predicting the behavior of road agents is a difficult and crucial task f...
In this paper, we propose a novel approach for agent motion prediction i...
Vehicle trajectory prediction is crucial for autonomous driving and adva...
Predicting the motion of a driver's vehicle is crucial for advanced driv...
Deep learning has revolutionized the ability to learn "end-to-end" auton...
Ego-centric data streams provide a unique opportunity to reason about jo...
The introduction of consumer RGB-D scanners set off a major boost in 3D
...