Method

FeedForwardNet [FFNet]
https://github.com/zcc31415926/FFNet

Submitted on 31 Aug. 2019 12:07 by
Jack Qian (Shanghai Jiao University)

Running time:1.07 s
Environment:GPU @ 1.5 Ghz (Python)

Method Description:
None
Parameters:
None
Latex Bibtex:
@article{zhao2019monocular,
title={Monocular Pedestrian Orientation Estimation Based on Deep 2D-3D Feedforward},
author={Zhao, Chenchen and Qian, Yeqiang and Yang, Ming},
journal={Pattern Recognition},
pages={107182},
year={2019},
publisher={Elsevier}
}

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) 87.17 % 75.81 % 69.86 %
Pedestrian (Orientation) 69.24 % 58.87 % 53.75 %
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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