Segmentation

Hypercorrelation Squeeze for Few-Shot Segmentation

Hypercorrelation Squeeze for Few-Shot Segmentation

This is the implementation of the paper “Hypercorrelation Squeeze for Few-Shot Segmentation” by Juhong Min, Dahyun Kang, and Minsu Cho. Implemented on Python 3.7 and Pytorch 1.5.1.

For more information, check out project [website] and the paper on [arXiv].

Requirements

  • Python 3.7
  • PyTorch 1.5.1
  • cuda 10.1
  • tensorboard 1.14

Conda environment settings:

conda create -n hsnet python=3.7
conda activate hsnet

conda install pytorch=1.5.1 torchvision cudatoolkit=10.1 -c pytorch
conda install -c conda-forge tensorflow
pip install tensorboardX

Preparing Few-Shot Segmentation Datasets

Download following datasets:

1. PASCAL-5i

Download PASCAL VOC2012 devkit (train/val data):

wget http://host.robots.ox.ac.uk/pascal/VOC/voc2012/VOCtrainval_11-May-2012.tar

Download PASCAL VOC2012 SDS extended mask annotations from our [Google Drive].

2. COCO-20i

Download COCO2014 train/val images

 

 

 

To finish reading, please visit source site