F2DNet is a Pedestron based repository which implements a novel, two-staged detector i.e. Fast Focal Detection Network for pedestrian detection.
Please refer to base repository for step-by-step installation.
In addition to configuration for different detectors provided in base repository we provide configuration for F2DNet.
Please refer to base repository for dataset preparation.
Dataset | ↓Reasonable | ↓Small | ↓Heavy |
---|---|---|---|
CityPersons | 8.7 | 11.3 | 32.6 |
EuroCityPersons | 6.1 | 10.7 | 28.2 |
Caltech Pedestrian | 2.2 | 2.5 | 38.7 |
Dataset | Config | Model | ↓Reasonable | ↓Small | ↓Heavy |
---|---|---|---|---|---|
CityPersons | cascade_hrnet | Cascade Mask R-CNN | 7.5 | 8.0 | 28.0 |
CityPersons | ecp_cp | F2DNet | 7.8 | 9.4 | 26.2 |
Caltech Pedestrian | cascade_hrnet | Cascade Mask R-CNN | 1.7 | 25.7 | |
Caltech Pedestrian | ecp_cp_caltech | F2DNet | 1.7 | 2.1 | 20.4 |
@Article{khan:2022,
author = {Khan, Abdul Hannan AND Munir, Mohsin AND Elst, Ludger van AND Dengel, Andreas},
title = {F2DNet: Fast Focal Detection Network for Pedestrian Detection},
version = {1},
date = {2022-03-04},
eprinttype = {arxiv},
eprintclass = {cs.CV, I.2.10; I.4.8; I.5.4},
eprint = {http://arxiv.org/abs/2203.02331v1},
url = {http://arxiv.org/abs/2203.02331v1}
}