2 citations · 2 across the 4 of their papers we have counts for
9 papers
Efficient Transformer-based 3D Object Detection with Dynamic Token Halting
Mao Ye, Gregory P. Meyer, Yuning Chai +1
Balancing efficiency and accuracy is a long-standing problem for deploying deep learning models. The trade-off is even more important for real-time safety-critical systems like aut…
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…
RV-FuseNet: Range View Based Fusion of Time-Series LiDAR Data for Joint 3D Object Detection and Motion Forecasting
Ankit Laddha, Shivam Gautam, Gregory P. Meyer +2
Robust real-time detection and motion forecasting of traffic participants is necessary for autonomous vehicles to safely navigate urban environments. In this paper, we present RV-F…
SDVTracker: Real-Time Multi-Sensor Association and Tracking for Self-Driving Vehicles
Shivam Gautam, Gregory P. Meyer, Carlos Vallespi-Gonzalez +1
Accurate motion state estimation of Vulnerable Road Users (VRUs), is a critical requirement for autonomous vehicles that navigate in urban environments. Due to their computational…
LaserFlow: Efficient and Probabilistic Object Detection and Motion Forecasting
Gregory P. Meyer, Jake Charland, Shreyash Pandey +4
In this work, we present LaserFlow, an efficient method for 3D object detection and motion forecasting from LiDAR. Unlike the previous work, our approach utilizes the native range…
An Alternative Probabilistic Interpretation of the Huber Loss
Gregory P. Meyer
The Huber loss is a robust loss function used for a wide range of regression tasks. To utilize the Huber loss, a parameter that controls the transitions from a quadratic function t…