Method

Channel-Spacial Fusion Awareness Detector [CSFADet]


Submitted on 24 Oct. 2019 10:54 by
Zhenjia Fan (Fuzhou University)

Running time:0.05 s
Environment:GPU @ 2.5 Ghz (Python)

Method Description:
Improve detection from centernet by CSFA module.
Parameters:
None
Latex Bibtex:
None

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) 93.75 % 88.54 % 78.62 %
Car (Orientation) 39.76 % 36.83 % 32.73 %
Pedestrian (Detection) 84.72 % 70.07 % 64.81 %
Pedestrian (Orientation) 46.75 % 38.41 % 35.44 %
Cyclist (Detection) 73.82 % 56.88 % 50.22 %
Cyclist (Orientation) 32.19 % 25.77 % 22.78 %
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



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



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



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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