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
arXiv PDF paper https://arxiv.org/pdf/2107.12518.pdf
GitHub https://github.com/warmspringwinds/segmentation_in_style
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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