
-
IntentNet: Learning to Predict Intention from Raw Sensor Data
In order to plan a safe maneuver, self-driving vehicles need to understa...
read it
-
MP3: A Unified Model to Map, Perceive, Predict and Plan
High-definition maps (HD maps) are a key component of most modern self-d...
read it
-
Deep Multi-Task Learning for Joint Localization, Perception, and Prediction
Over the last few years, we have witnessed tremendous progress on many s...
read it
-
End-to-end Interpretable Neural Motion Planner
In this paper, we propose a neural motion planner (NMP) for learning to ...
read it
-
TrafficSim: Learning to Simulate Realistic Multi-Agent Behaviors
Simulation has the potential to massively scale evaluation of self-drivi...
read it
-
Diverse Complexity Measures for Dataset Curation in Self-driving
Modern self-driving autonomy systems heavily rely on deep learning. As a...
read it
-
AdvSim: Generating Safety-Critical Scenarios for Self-Driving Vehicles
As self-driving systems become better, simulating scenarios where the au...
read it
-
LookOut: Diverse Multi-Future Prediction and Planning for Self-Driving
Self-driving vehicles need to anticipate a diverse set of future traffic...
read it
-
Safety-Oriented Pedestrian Motion and Scene Occupancy Forecasting
In this paper, we address the important problem in self-driving of forec...
read it
-
StrObe: Streaming Object Detection from LiDAR Packets
Many modern robotics systems employ LiDAR as their main sensing modality...
read it
-
Perceive, Predict, and Plan: Safe Motion Planning Through Interpretable Semantic Representations
In this paper we propose a novel end-to-end learnable network that perfo...
read it
-
RadarNet: Exploiting Radar for Robust Perception of Dynamic Objects
We tackle the problem of exploiting Radar for perception in the context ...
read it
-
Implicit Latent Variable Model for Scene-Consistent Motion Forecasting
In order to plan a safe maneuver an autonomous vehicle must accurately p...
read it
-
The Importance of Prior Knowledge in Precise Multimodal Prediction
Roads have well defined geometries, topologies, and traffic rules. While...
read it
-
PnPNet: End-to-End Perception and Prediction with Tracking in the Loop
We tackle the problem of joint perception and motion forecasting in the ...
read it
-
Spatially-Aware Graph Neural Networks for Relational Behavior Forecasting from Sensor Data
In this paper, we tackle the problem of relational behavior forecasting ...
read it
-
Discrete Residual Flow for Probabilistic Pedestrian Behavior Prediction
Self-driving vehicles plan around both static and dynamic objects, apply...
read it