Honda Egocentric View-Intersection Dataset
Honda Egocentric View-Intersection Dataset (HEV-I) is introduced to enable research on traffic participants interaction modelling, future object localization, as well as learning driver action in challenging driving scenarios. The dataset includes 230 video clips of real human driving in different intersections from the San Francisco Bay Area, collected using an instrumented vehicle equipped with different sensors including cameras, GPS/IMU, and vehicle states signals.
Variants: HEV-I
This dataset is used in 1 benchmark:
Task | Model | Paper | Date |
---|---|---|---|
Trajectory Prediction | SGNet | Stepwise Goal-Driven Networks for Trajectory … | 2021-03-25 |
Trajectory Prediction | FOL-X | Unsupervised Traffic Accident Detection in … | 2019-03-02 |
Recent papers with results on this dataset: