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A PyTorch implementation of paper "PFENet: Prior Guided Feature Enrichment Network for Few-shot Segmentation".

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PFENet

This is the implementation of the good work PFENet: Prior Guided Feature Enrichment Network for Few-shot Segmentation. Based on this paper, we rewrite the code for higher training efficiency and better code reuse. Thanks to the official implementation.

Dataset

In this paper, PASCAL-5i and COCO 2014 are used for evaluation.

We have preprocessed PASCAL-5i, and you can download (pass code: b74i) it directly.

All datasets are stored in DocSet (*.ds) files, since this file format is portable and efficient. To support ds files in your system, install the "dcoset" package for your python environment.

pip3 install docset

Run The Code

python3 train.py --data-path /path/of/pascal5i.ds --gpu 0 --batch-size 8 --num-epochs 30

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A PyTorch implementation of paper "PFENet: Prior Guided Feature Enrichment Network for Few-shot Segmentation".

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