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Portrait Segmentation in PyTorch

Based on Automatic Portrait Segmentation for Image Stylization (Shen et al. 2016)
Implemented as a final project for CS690IV Intelligent Visual Computing. University of Massachusetts Amherst. Spring 2018.

Notes and Instructions

FCN.py contains a PyTorch implementation of FCN-8s (Long et al. 2015), using the convolutional part of the model architecture of VGG-16 (Simonyan et al. 2014).

Execute using python run.py

train() and test() methods are in trainer.py

Code is meant for the data from Shen et al. The data is handled through DataLoader.py for this particular dataset. Modifications to this file might be necessary to adapt to a different dataset.

References

Long, J., Shelhamer, E. and Darrell, T., 2015. Fully convolutional networks for semantic segmentation. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 3431-3440).

Shen, X., Hertzmann, A., Jia, J., Paris, S., Price, B., Shechtman, E. and Sachs, I., 2016, May. Automatic portrait segmentation for image stylization. In Computer Graphics Forum (Vol. 35, No. 2, pp. 93-102). (Data and Caffe implementation available at http://xiaoyongshen.me/webpage_portrait/index.html)

Simonyan, K. and Zisserman, A., 2014. Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556.

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690IV Intelligent Visual Computing Project

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