Argoverse: 3d tracking and forecasting with rich maps
We present Argoverse, a dataset designed to support autonomous vehicle perception tasks
including 3D tracking and motion forecasting. Argoverse includes sensor data collected by a …
including 3D tracking and motion forecasting. Argoverse includes sensor data collected by a …
Scene transformer: A unified architecture for predicting multiple agent trajectories
Predicting the motion of multiple agents is necessary for planning in dynamic environments.
This task is challenging for autonomous driving since agents (eg vehicles and pedestrians) …
This task is challenging for autonomous driving since agents (eg vehicles and pedestrians) …
Stopnet: Scalable trajectory and occupancy prediction for urban autonomous driving
We introduce a motion forecasting (behavior prediction) method that meets the latency
requirements for autonomous driving in dense urban environments without sacrificing …
requirements for autonomous driving in dense urban environments without sacrificing …
Unlimited neighborhood interaction for heterogeneous trajectory prediction
Understanding complex social interactions among agents is a key challenge for trajectory
prediction. Most existing methods consider the interactions between pairwise traffic agents …
prediction. Most existing methods consider the interactions between pairwise traffic agents …
Uncertainty-aware short-term motion prediction of traffic actors for autonomous driving
We address one of the crucial aspects necessary for safe and efficient operations of
autonomous vehicles, namely predicting future state of traffic actors in the autonomous …
autonomous vehicles, namely predicting future state of traffic actors in the autonomous …
Heterogeneous-agent trajectory forecasting incorporating class uncertainty
Reasoning about the future behavior of other agents is critical to safe robot navigation. The
multiplicity of plausible futures is further amplified by the uncertainty inherent to agent state …
multiplicity of plausible futures is further amplified by the uncertainty inherent to agent state …
Occupancy flow fields for motion forecasting in autonomous driving
We propose Occupancy Flow Fields, a new representation for motion forecasting of multiple
agents, an important task in autonomous driving. Our representation is a spatio-temporal …
agents, an important task in autonomous driving. Our representation is a spatio-temporal …
Motionnet: Joint perception and motion prediction for autonomous driving based on bird's eye view maps
The ability to reliably perceive the environmental states, particularly the existence of objects
and their motion behavior, is crucial for autonomous driving. In this work, we propose an …
and their motion behavior, is crucial for autonomous driving. In this work, we propose an …
Spatio-temporal gating-adjacency gcn for human motion prediction
Predicting future motion based on historical motion sequence is a fundamental problem in
computer vision, and it has wide applications in autonomous driving and robotics. Some …
computer vision, and it has wide applications in autonomous driving and robotics. Some …
Stochastic scene-aware motion prediction
A long-standing goal in computer vision is to capture, model, and realistically synthesize
human behavior. Specifically, by learning from data, our goal is to enable virtual humans to …
human behavior. Specifically, by learning from data, our goal is to enable virtual humans to …