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Feature Pyramid Networks for Object Detection

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Feature Pyramid Network on caffe

This is the unoffical version Feature Pyramid Network for Feature Pyramid Networks for Object Detection


FPN(resnet50)-end2end result is implemented without OHEM and train with pascal voc 2007 + 2012 test on 2007

merged rcnn

|[email protected]|aeroplane|bicycle|bird|boat|bottle|bus|car|cat|chair|cow| |:--:|:-------:| -----:| --:| --:|-----:|--:|--:|--:|----:|--:| |0.788|0.8079| 0.8036| 0.8010| 0.7293|0.6743|0.8680|0.8766|0.8967|0.6122|0.8646|

|diningtable|dog |horse|motorbike|person |pottedplant|sheep|sofa|train|tv| |----------:|:--:|:---:| -------:| -----:| -------:|----:|---:|----:|--:| |0.7330|0.8855|0.8760| 0.8063| 0.7999| 0.5138|0.7905|0.7755|0.8637|0.7736|

shared rcnn

|[email protected]|aeroplane|bicycle|bird|boat|bottle|bus|car|cat|chair|cow| |:--:|:-------:| -----:| --:| --:|-----:|--:|--:|--:|----:|--:| |0.7833|0.8585| 0.8001| 0.7970| 0.7174|0.6522|0.8668|0.8768|0.8929|0.5842|0.8658|

|diningtable|dog |horse|motorbike|person |pottedplant|sheep|sofa|train|tv| |----------:|:--:|:---:| -------:| -----:| -------:|----:|---:|----:|--:| |0.7022|0.8891|0.8680| 0.7991| 0.7944| 0.5065|0.7896|0.7707|0.8697|0.7653|


megred rcnn framework

Network overview: link

shared rcnn

Network overview: link

the red and yellow are shared params

about the anchor size setting

In the paper the anchor setting is

Ratios: [0.5,1,2],scales :[8,]

With the setting and P2~P6, all anchor sizes are

,but this setting is suit for COCO dataset which has so many small targets.

But the voc dataset targets are range


So, we desgin the anchor setting:

Ratios: [0.5,1,2],scales :[8,16]
, this is very import for voc dataset.


download voc07,12 dataset

and rename to
cp ResNet50.v2.caffemodel data/pretrained_model/
  • OneDrive download: link

In my expriments, the codes require ~10G GPU memory in training and ~6G in testing. 
your can design the suit image size, mimbatch size and rcnn batch size for your GPUS.

compile caffe & lib

cd caffe-fpn
mkdir build
cd build
cmake ..
make -j16 all
cd lib

train & test

shared rcnn

./experiments/scripts/ 1 FPN pascal_voc
./ 1 FPN pascal_voc
megred rcnn
 ./experiments/scripts/ 0 FPN pascal_voc
 ./ 0 FPN pascal_voc
0 1 is GPU id.


  • [x] all tests passed
  • [x] evaluate object detection performance on voc
  • [x] evaluate merged rcnn version performance on voc

feature pyramid networks for object detection

Lin, T. Y., Dollár, P., Girshick, R., He, K., Hariharan, B., & Belongie, S. (2016). Feature pyramid networks for object detection. arXiv preprint arXiv:1612.03144.

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