ETH Pedestrian
ETH is a dataset for pedestrian detection. The testing set contains 1,804 images in three video clips. The dataset is captured from a stereo rig mounted on car, with a resolution of 640 x 480 (bayered), and a framerate of 13--14 FPS.
Source: Scale-aware Fast R-CNN for Pedestrian Detection
Image Source: https://medium.com/@zhenqinghu/pedestrian-detection-on-eth-data-set-with-faster-r-cnn-19d0a906f1d3
Variants: ETH BIWI Walking Pedestrians dataset, ETH/UCY, ETH
This dataset is used in 1 benchmark:
| Task | Model | Paper | Date |
|---|---|---|---|
| Trajectory Prediction | Social-Implicit | Social-Implicit: Rethinking Trajectory Prediction Evaluation … | 2022-03-06 |
| Trajectory Prediction | Social-STGCNN | Social-STGCNN: A Social Spatio-Temporal Graph … | 2020-02-27 |
| Trajectory Prediction | Trajectron++ | Trajectron++: Dynamically-Feasible Trajectory Forecasting With … | 2020-01-09 |
| Trajectory Prediction | Social-GAN | Social GAN: Socially Acceptable Trajectories … | 2018-03-29 |
Recent papers with results on this dataset: