Researching | Improved Algorithm Based on Feature Pyramid Networks

Laser & Optoelectronics Progress, Volume. 56, Issue 21, 211505(2019)

Improved Algorithm Based on Feature Pyramid Networks

Jingming Chen, Jie Jin^*, and Weifeng Wang

Author Affiliations

School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China

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Figures&Tables (7)

References (19)

Paper Information

Figures & Tables(7)

Fig. 1. Overall network structure of Refine-FPN algorithm

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Fig. 2. Basic structure of prediction optimization module

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Fig. 3. Test results

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Table 1. Comparison between Refine-FPN and other classical algorithms

Table 1. Comparison between Refine-FPN and other classical algorithms

Method	Training set	Backbone	Accuracy /%
Method	Training set	Backbone	IOU of 0.5	IOU of 0.6	IOU of 0.75
SSD	VOC07+12	VGG-16	77.3	72.3	61.3
RFCN	VOC07+12	ResNet-101	80.5	73.2	61.8
Faster Rcnn	VOC07+12	ResNet-101	76.4	69.5	57.3
YOLOv2	VOC07+12	Darknet-19	78.6	69.1	56.5
FPN	VOC07+12	ResNet-101	80.5	-	-
Couplenet	VOC07+12	ResNet-101	81.7	-	-
Res101-RFCN-Cascade	VOC07+12	ResNet-101	79.6	-	59.2
BPN512	VOC07+12	VGG-16	81.9	77.6	68.3
Refine-FPN	VOC07+12	Detnet-59	80.9	74.4	65.3
FPN^*	VOC07+12	Detnet-59	79.8	-	-

Table 2. Specific test results on VOC2007%

Table 2. Specific test results on VOC2007%

Method	mAP	Bike	Boat	Bottle	TV	Chair	Table	Sheep	Train	Cat
SSD	77.3	83.9	69.6	50.5	76.8	60.3	77.0	77.9	87.6	88.1
RFCN	80.5	89.6	69.0	69.2	79.5	65.4	72.1	79.6	87.1	88.4
Faster Rcnn	76.4	80.7	68.3	55.9	72.0	56.7	69.4	78.6	85.3	85.3
FPN	80.5	80.1	72.9	67.4	72.3	61.5	68.7	78.3	87.4	87.3
Couplenet	81.7	86.0	74.5	72.3	80.1	68.8	75.6	81.9	86.7	88.5
Refine-FPN	80.9	80.4	73.8	70.5	73.1	63.3	69.8	79.1	87.6	87.8

Table 3. Comparison results when different prediction networks are cascaded in FPN^* algorithm
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Table 3. Comparison results when different prediction networks are cascaded in FPN^* algorithm
Stage Accuracy (IOU of 0.5) /%
First stage (IOU of 0.5) 79.8
Second stage(IOU of 0.6) 80.3
Third stage(IOU of 0.75) 80.5
Fourth stage(IOU of 0.8) 80.4

Table 4. Comparison results when different contextual information are combined in FPN^* algorithm
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Table 4. Comparison results when different contextual information are combined in FPN^* algorithm
Context information Accuracy (IOU of 0.5) /%
ROI(×1) 79.8
ROI(×0.8, ×1) 80.0
ROI(×1, ×1.2) 80.1
ROI(×0.8, ×1, ×1.2) 80.3

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Jingming Chen, Jie Jin, Weifeng Wang. Improved Algorithm Based on Feature Pyramid Networks[J]. Laser & Optoelectronics Progress, 2019, 56(21): 211505

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Paper Information

Category: Machine Vision

Received: Mar. 21, 2019

Accepted: Apr. 30, 2019

Published Online: Nov. 2, 2019

The Author Email: Jin Jie (jinjie@tju.edu.cn)

DOI:10.3788/LOP56.211505

Topics

laser devices and laser physics

Lasers and Laser Optics

laser manufacturing

Instrumentation, Measurement and Metrology