Method

Region Proposal Network + Boost Forest [RPN+BF]
https://github.com/zhangliliang/RPN_BF/tree/RPN-pedestrian

Submitted on 27 Feb. 2016 07:30 by
Liliang Zhang (SYSU)

Running time:0.6 s
Environment:GPU @ 2.5 Ghz (Matlab + C/C++)

Method Description:
Parameters:
Latex Bibtex:
@inproceedings{Zhang2016ECCV,
title={Is Faster R-CNN Doing Well for Pedestrian
Detection?},
author={Zhang, Liliang and Lin, Liang and Liang,
Xiaodan and He, Kaiming},
journal={ECCV},
year={2016}
}

Detailed Results

Object detection and orientation estimation results. Results for object detection are given in terms of average precision (AP) and results for joint object detection and orientation estimation are provided in terms of average orientation similarity (AOS).


Benchmark Easy Moderate Hard
Pedestrian (Detection) 77.06 % 61.22 % 55.22 %
Pedestrian (Orientation) 41.19 % 32.12 % 28.83 %
This table as LaTeX

2D object detection results.
This figure as: png eps pdf txt gnuplot



Orientation estimation results.
This figure as: png eps pdf txt gnuplot




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