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Unsupervised segmentation of image into parts

Unsupervised segmentation of image into parts


Segmentation in Style: Unsupervised Semantic Image Segmentation with Stylegan and CLIP

arXiv paper abstract https://arxiv.org/abs/2107.12518





We introduce a method that allows to automatically segment images into semantically meaningful regions without human supervision.


... we use pretrained StyleGAN2 generative model: clustering in the feature space of the generative model allows to discover semantic classes.


Once classes are discovered, a synthetic dataset with generated images and corresponding segmentation masks can be created.


After that a segmentation model is trained on the synthetic dataset and is able to generalize to real images.


Additionally, by using CLIP we are able to use prompts defined in a natural language to discover some desired semantic classes. ...



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