Face-Trace: Open-Set Attribution and Progressive Discovery of Synthetic Face Generators
Recent advances in generative Artificial Intelligence have made synthetic face images increasingly realistic, creating new challenges for multimedia forensics. Source attribution methods should identify the generator of an image when the source is known, but also handle samples produced by unseen models. Most existing approaches, however, address synthetic face attribution in a closed-set setting, assuming that test samples can only originate from generators observed during training. This assumption does not hold in real-world scenarios, where new generators continuously appear and detecting an image as unknown is not sufficient, since rejected samples should also be organized according t...
| Authors | Alessia Infantino, Claudio Schiavella, Irene Amerini |
|---|---|
| Primary category | cs.CV |
| Published | 8 July 2026 |
| Last updated at source | 29 July 2026 |
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