mlsanityData to 7 Oct 2026

Darker than Black-Box: Face Reconstruction from Similarity Queries

arXiv 2106.14290 ↗First posted 27 Jun 2021cs.CVcited by 6

Not on the map. Why?

Abstract (arXiv)

Several methods for inversion of face recognition models were recently presented, attempting to reconstruct a face from deep templates. Although some of these approaches work in a black-box setup using only face embeddings, usually, on the end-user side, only similarity scores are provided. Therefore, these algorithms are inapplicable in such scenarios. We propose a novel approach that allows reconstructing the face querying only similarity scores of the black-box model. While our algorithm operates in a more general setup, experiments show that it is query efficient and outperforms the existing methods.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 15 of its 25 references that are in the map. First posted on arXiv 27 Jun 2021.

Builds on

15 of 25 references.

References · 15

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  9. 2018Deep Face Recognition: A Surveycited by 275
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  12. 2017On the Reconstruction of Face Images from Deep Face Templatescited by 66
3 more
  1. 2020Vec2Face: Unveil Human Faces from their Blackbox Features in Face Recognitioncited by 36
  2. 2020Black-Box Face Recovery from Identity Featurescited by 20
  3. 2018Inverting Supervised Representations with Autoregressive Neural Density Modelscited by 12

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 2; 2023: 0; 2024: 2; 2025: 0; 2026: 2.

6 papers.