liuzhongling / ASSD-Pytorch

ASSD learns to highlight useful regions on the feature maps while suppressing the irrelevant information, thereby providing reliable guidance for object detection.

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ASSD-Pytorch

Please cite the article in your publications if it helps your research (Arxiv Link, ELSEVIER Link):

@article{YI2019102827,
    title = "ASSD: Attentive single shot multibox detector",
    journal = "Computer Vision and Image Understanding",
    pages = "102827",
    year = "2019",
    issn = "1077-3142",
    doi = "https://doi.org/10.1016/j.cviu.2019.102827",
    url = "http://www.sciencedirect.com/science/article/pii/S1077314219301328",
    author = "Jingru Yi and Pengxiang Wu and Dimitris N. Metaxas",
}

ASSD learns to highlight useful regions on the feature maps while suppressing the irrelevant information, thereby providing reliable guidance for object detection.

System VOC2007 test VOC2012 test FPS (TitanX) #Boxes Input resolution
SSD300 (VGG16) 77.2 75.8 46 8732 300 x 300
SSD512 (VGG16) 79.8 78.5 19 24564 512 x 512
ASSD300 (VGG16) 80.0 77.5 - 8732 300 x 300
ASSD321 (ResNet101) 79.5 76.4 27.5 10325 321 x 321
ASSD512 (VGG16) 81.6 80.0 - 24564 512 x 512
ASSD513 (ResNet101) 83.0 81.3 16 25844 513 x 513

Dependencies

Library: OpenCV-Python, PyTorch>0.4.0, Ubuntu 14.04

Dataset

PascalVOC

# Download the data.
cd $HOME/data
wget http://host.robots.ox.ac.uk/pascal/VOC/voc2012/VOCtrainval_11-May-2012.tar
wget http://host.robots.ox.ac.uk/pascal/VOC/voc2007/VOCtrainval_06-Nov-2007.tar
wget http://host.robots.ox.ac.uk/pascal/VOC/voc2007/VOCtest_06-Nov-2007.tar
# Extract the data.
tar -xvf VOCtrainval_11-May-2012.tar
tar -xvf VOCtrainval_06-Nov-2007.tar
tar -xvf VOCtest_06-Nov-2007.tar

MSCOCO 2017 (download link)

  #step1: download the following data and annotation
  2017 Train images [118K/18GB]
  2017 Val images [5K/1GB]
  2017 Test images [41K/6GB]
  2017 Train/Val annotations [241MB]
  #step2: arrange the data to the following structure
  COCO
  ---train
  ---test
  ---val
  ---annotations

Train/Test/Evaluation

This is a simplified version. The full version will be released later.
1. Change the mode in main.py
2. Change parameters such as root (data directory) in config.py
3. python main.py

About

ASSD learns to highlight useful regions on the feature maps while suppressing the irrelevant information, thereby providing reliable guidance for object detection.


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