F2DNet

F2DNet is a Pedestron based repository which implements a novel, two-staged detector i.e. Fast Focal Detection Network for pedestrian detection.

Installation

Please refer to base repository for step-by-step installation.

List of detectors

In addition to configuration for different detectors provided in base repository we provide configuration for F2DNet.

Following datasets are currently supported

• Caltech
• CityPersons
• EuroCity Persons

Datasets Preparation

Please refer to base repository for dataset preparation.

Benchmarking

Benchmarking of F2DNet on pedestrian detection datasets

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

Benchmarking of F2DNet when trained using extra data on pedestrian detection datasets

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

References

• Pedestron

Please cite the following work

AxXiv2022

@inproceedings{khan2022f2dnet,
  title={F2DNet: fast focal detection network for pedestrian detection},
  author={Khan, Abdul Hannan and Munir, Mohsin and van Elst, Ludger and Dengel, Andreas},
  booktitle={2022 26th International Conference on Pattern Recognition (ICPR)},
  pages={4658--4664},
  year={2022},
  organization={IEEE}
}