Papers › Adversarially-Guided Portrait Matting
Adversarially-Guided Portrait Matting
Sergej Chicherin, Karen Efremyan
We present a method for generating alpha mattes using a limited data source. We pretrain a novel transformerbased model (StyleMatte) on portrait datasets. We utilize this model to provide image-mask pairs for the StyleGAN3-based network (StyleMatteGAN). This network is trained unsupervisedly and generates previously unseen imagemask training pairs that are fed back to StyleMatte. We demonstrate that the performance of the matte pulling network improves during this cycle and obtains top results on the human portraits and state-of-the-art metrics on animals dataset. Furthermore, StyleMatteGAN provides high-resolution, privacy-preserving portraits with alpha mattes, making it suitable for various image composition tasks. Our code is available at https://github.com/chroneus/stylematte
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Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Image Matting | AM-2K | StyleMatte | MAD | 0.0055 | #1 of 9 | Archive leaderboard | report |
| Image Matting | AM-2K | StyleMatte | MSE | 0.0024 | #1 of 9 | Archive leaderboard | report |
| Image Matting | AM-2K | StyleMatte | SAD | 9.602 | #1 of 9 | Archive leaderboard | report |
| Image Matting | P3M-10k | StyleMatte | MAD | 0.004 | #2 of 7 | Archive leaderboard | report |
| Image Matting | P3M-10k | StyleMatte | MSE | 0.0019 | #2 of 7 | Archive leaderboard | report |
| Image Matting | P3M-10k | StyleMatte | SAD | 6.97 | #2 of 7 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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