activity
20172026
most citedUncertainty-Aware Driver Trajectory Prediction at Urban Intersections

11 citations · 20 across the 22 of their papers we have counts for

collaborators
Showing 2021Show all

6 papers · 1 filter

cs.HC2021

MAAD: A Model and Dataset for "Attended Awareness" in Driving

Deepak Gopinath, Guy Rosman, Simon Stent +4

We propose a computational model to estimate a person's attended awareness of their environment. We define attended awareness to be those parts of a potentially dynamic scene which…

cs.RO2021

HYPER: Learned Hybrid Trajectory Prediction via Factored Inference and Adaptive Sampling

Xin Huang, Guy Rosman, Igor Gilitschenski +4

Modeling multi-modal high-level intent is important for ensuring diversity in trajectory prediction. Existing approaches explore the discrete nature of human intent before predicti…

cs.RO2021

Trajectory Prediction with Linguistic Representations

Yen-Ling Kuo, Xin Huang, Andrei Barbu +4

Language allows humans to build mental models that interpret what is happening around them resulting in more accurate long-term predictions. We present a novel trajectory predictio…

cs.RO2021

TIP: Task-Informed Motion Prediction for Intelligent Vehicles

Xin Huang, Guy Rosman, Ashkan Jasour +3

When predicting trajectories of road agents, motion predictors usually approximate the future distribution by a limited number of samples. This constraint requires the predictors t…

cs.LG2021

Risk Conditioned Neural Motion Planning

Xin Huang, Meng Feng, Ashkan Jasour +2

Risk-bounded motion planning is an important yet difficult problem for safety-critical tasks. While existing mathematical programming methods offer theoretical guarantees in the co…

cs.CV2021

SUPR-GAN: SUrgical PRediction GAN for Event Anticipation in Laparoscopic and Robotic Surgery

Yutong Ban, Guy Rosman, Jennifer A. Eckhoff +6

Comprehension of surgical workflow is the foundation upon which artificial intelligence (AI) and machine learning (ML) holds the potential to assist intraoperative decision-making…