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arXiv Computer Vision By \"Unsal \"Ozt\"urk, Vedrana Krivoku\'ca Hahn, Sushil Bhattacharjee, S\'ebastien Marcel

Damnatio Memoriae: Adversarially and Selectively Forgetting Identities in the Embedding Space of Face Recognition Models

Read the original on arXiv Computer Vision →

The paper introduces "open‑set adversarial forgetting" to make selected identities unlinkable in face recognition models while keeping the system functional for other users. Three loss functions are proposed: one disperses embeddings from their centroid, and two map each image to a near‑orthogonal target—either learned via the classifier head or fixed as an almost‑orthonormal frame. Experiments on multiple backbones and forget scales show that these losses, especially the orthonormal‑frame approach, effectively render the targeted identities unidentifiable and outperform prior methods while preserving higher retain rates.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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