Inverting Black-Box Face Recognition Systems via Zero-Order Optimization in Eigenface Space
Fuente:
arXiv
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| Autori principali: | , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866913889335115776 |
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| author | Razzhigaev, Anton Mikhalchuk, Matvey Kireev, Klim Udovichenko, Igor Kuznetsov, Andrey Petiushko, Aleksandr |
| author_facet | Razzhigaev, Anton Mikhalchuk, Matvey Kireev, Klim Udovichenko, Igor Kuznetsov, Andrey Petiushko, Aleksandr |
| contents | Reconstructing facial images from black-box recognition models poses a significant privacy threat. While many methods require access to embeddings, we address the more challenging scenario of model inversion using only similarity scores. This paper introduces DarkerBB, a novel approach that reconstructs color faces by performing zero-order optimization within a PCA-derived eigenface space. Despite this highly limited information, experiments on LFW, AgeDB-30, and CFP-FP benchmarks demonstrate that DarkerBB achieves state-of-the-art verification accuracies in the similarity-only setting, with competitive query efficiency. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_09777 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Inverting Black-Box Face Recognition Systems via Zero-Order Optimization in Eigenface Space Razzhigaev, Anton Mikhalchuk, Matvey Kireev, Klim Udovichenko, Igor Kuznetsov, Andrey Petiushko, Aleksandr Computer Vision and Pattern Recognition Artificial Intelligence Reconstructing facial images from black-box recognition models poses a significant privacy threat. While many methods require access to embeddings, we address the more challenging scenario of model inversion using only similarity scores. This paper introduces DarkerBB, a novel approach that reconstructs color faces by performing zero-order optimization within a PCA-derived eigenface space. Despite this highly limited information, experiments on LFW, AgeDB-30, and CFP-FP benchmarks demonstrate that DarkerBB achieves state-of-the-art verification accuracies in the similarity-only setting, with competitive query efficiency. |
| title | Inverting Black-Box Face Recognition Systems via Zero-Order Optimization in Eigenface Space |
| topic | Computer Vision and Pattern Recognition Artificial Intelligence |
| url | https://arxiv.org/abs/2506.09777 |