Method

Integrating YOLO with FCN [Int-YOLO]
https://github.com/placeforyiming/DeepLearning_PerceptionSystem

Submitted on 28 Dec. 2018 21:17 by
Yiming Zhao (Worcester Polytechnic Institute)

Running time:0.03 s
Environment:1 core @ 2.5 Ghz (C/C++)

Method Description:
I extract tensor from FCN to provide detection part the
semantic information. The model can do semantic
segmentation and object detection together with real time
performace.
Parameters:
\alpha=0.4 for NMS
Latex Bibtex:
coming soon

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
Car (Detection) 75.81 % 73.23 % 63.59 %
Pedestrian (Detection) 64.09 % 48.76 % 44.31 %
Cyclist (Detection) 53.34 % 39.83 % 34.16 %
This table as LaTeX


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



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



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




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