/F2DNet

[F2DNet] Fast Focal Detection Network for Pedestrian Detection

Primary LanguagePythonApache License 2.0Apache-2.0

PWC

PWC

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

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

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}
}