38 citations · 124 across the 28 of their papers we have counts for
6 papers · 1 filter
Coupling Intent and Action for Pedestrian Crossing Behavior Prediction
Yu Yao, Ella Atkins, Matthew Johnson Roberson +2
Accurate prediction of pedestrian crossing behaviors by autonomous vehicles can significantly improve traffic safety. Existing approaches often model pedestrian behaviors using tra…
Polylidar3D -- Fast Polygon Extraction from 3D Data
Jeremy Castagno, Ella Atkins
Flat surfaces captured by 3D point clouds are often used for localization, mapping, and modeling. Dense point cloud processing has high computation and memory costs making low-dime…
BiTraP: Bi-directional Pedestrian Trajectory Prediction with Multi-modal Goal Estimation
Yu Yao, Ella Atkins, Matthew Johnson-Roberson +2
Pedestrian trajectory prediction is an essential task in robotic applications such as autonomous driving and robot navigation. State-of-the-art trajectory predictors use a conditio…
When, Where, and What? A New Dataset for Anomaly Detection in Driving Videos
Yu Yao, Xizi Wang, Mingze Xu +3
Video anomaly detection (VAD) has been extensively studied. However, research on egocentric traffic videos with dynamic scenes lacks large-scale benchmark datasets as well as effec…
Unsupervised Traffic Accident Detection in First-Person Videos
Yu Yao, Mingze Xu, Yuchen Wang +2
Recognizing abnormal events such as traffic violations and accidents in natural driving scenes is essential for successful autonomous driving and advanced driver assistance systems…
Egocentric Vision-based Future Vehicle Localization for Intelligent Driving Assistance Systems
Yu Yao, Mingze Xu, Chiho Choi +3
Predicting the future location of vehicles is essential for safety-critical applications such as advanced driver assistance systems (ADAS) and autonomous driving. This paper introd…