75 citations · 183 across the 19 of their papers we have counts for
7 papers · 1 filter
Detection of Active Emergency Vehicles using Per-Frame CNNs and Output Smoothing
Meng Fan, Craig Bidstrup, Zhaoen Su +3
While inferring common actor states (such as position or velocity) is an important and well-explored task of the perception system aboard a self-driving vehicle (SDV), it may not a…
Convolutions for Spatial Interaction Modeling
Zhaoen Su, Chao Wang, David Bradley +3
In many different fields interactions between objects play a critical role in determining their behavior. Graph neural networks (GNNs) have emerged as a powerful tool for modeling…
Uncertainty-Aware Vehicle Orientation Estimation for Joint Detection-Prediction Models
Henggang Cui, Fang-Chieh Chou, Jake Charland +2
Object detection is a critical component of a self-driving system, tasked with inferring the current states of the surrounding traffic actors. While there exist a number of studies…
Ellipse Loss for Scene-Compliant Motion Prediction
Henggang Cui, Hoda Shajari, Sai Yalamanchi +1
Motion prediction is a critical part of self-driving technology, responsible for inferring future behavior of traffic actors in autonomous vehicle's surroundings. In order to ensur…
Temporally-Continuous Probabilistic Prediction using Polynomial Trajectory Parameterization
Zhaoen Su, Chao Wang, Henggang Cui +3
A commonly-used representation for motion prediction of actors is a sequence of waypoints (comprising positions and orientations) for each actor at discrete future time-points. Whi…
Multi-View Fusion of Sensor Data for Improved Perception and Prediction in Autonomous Driving
Sudeep Fadadu, Shreyash Pandey, Darshan Hegde +4
We present an end-to-end method for object detection and trajectory prediction utilizing multi-view representations of LiDAR returns and camera images. In this work, we recognize t…
MultiXNet: Multiclass Multistage Multimodal Motion Prediction
Nemanja Djuric, Henggang Cui, Zhaoen Su +13
One of the critical pieces of the self-driving puzzle is understanding the surroundings of a self-driving vehicle (SDV) and predicting how these surroundings will change in the nea…