Abdal, Rameen;
Zhu, Peihao;
Mitra, Niloy J;
Wonka, Peter;
(2022)
Labels4Free: Unsupervised Segmentation using StyleGAN.
In:
2021 IEEE/CVF International Conference on Computer Vision (ICCV).
(pp. pp. 13950-13959).
IEEE: Montreal, QC, Canada.
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Abstract
We propose an unsupervised segmentation framework for StyleGAN generated objects. We build on two main observations. First, the features generated by StyleGAN hold valuable information that can be utilized towards training segmentation networks. Second, the foreground and background can often be treated to be largely independent and be swapped across images to produce plausible composited images. For our solution, we propose to augment the StyleGAN2 generator architecture with a segmentation branch and to split the generator into a foreground and background network. This enables us to generate soft segmentation masks for the foreground object in an unsupervised fashion. On multiple object classes, we report comparable results against state-of-the-art supervised segmentation networks, while against the best unsupervised segmentation approach we demonstrate a clear improvement, both in qualitative and quantitative metrics. Project Page: https:/rameenabdal.github.io/Labels4Free.
| Type: | Proceedings paper |
|---|---|
| Title: | Labels4Free: Unsupervised Segmentation using StyleGAN |
| Event: | 18th IEEE/CVF International Conference on Computer Vision (ICCV) |
| Location: | ELECTR NETWORK |
| Dates: | 11 Oct 2021 - 17 Oct 2021 |
| ISBN-13: | 9781665428125 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/ICCV48922.2021.01371 |
| Publisher version: | https://doi.org/10.1109/ICCV48922.2021.01371 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Science & Technology, Technology, Computer Science, Artificial Intelligence, Computer Science, Theory & Methods, Computer Science |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10159078 |
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