Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models | Paper Citation Record

Observation 5218b61b-765c-4077-b6c0-20db4bfd1056 · outbound

This paper cites Secure face matching using fully homomorphic encryption.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models Secure face matching using fully homomorphic encryption

Reference 1

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Observation b54010d4-f560-48c7-8a8e-0d568b6b8b84 · outbound

This paper cites Sface: Privacy-friendly and accurate face recognition using synthetic data.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models Sface: Privacy-friendly and accurate face recognition using synthetic data

Reference 2

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This paper cites Privacy pre- serving face recognition utilizing differential privacy.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models Privacy pre- serving face recognition utilizing differential privacy

Reference 3

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Observation 6e5cc1c0-d181-4aa8-856d-5c9f3e6b6204 · outbound

This paper cites Arcface: Additive angular margin loss for deep face recognition.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models Arcface: Additive angular margin loss for deep face recognition

Reference 4

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This paper cites Inverting visual rep- resentations with convolutional networks.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models Inverting visual rep- resentations with convolutional networks

Reference 5

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This paper cites Model inversion attacks that exploit confidence information and basic countermeasures.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models Model inversion attacks that exploit confidence information and basic countermeasures

Reference 6

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This paper cites ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness

Reference 7

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This paper cites Deep residual learning for image recognition.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models Deep residual learning for image recognition

Reference 8

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Observation 6e9c7ac0-a927-44aa-9761-ed41307d98c5 · outbound

This paper cites Model inver- sion attacks against collaborative inference.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models Model inver- sion attacks against collaborative inference

Reference 9

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Observation 8e1c729d-aea7-4739-8bbd-42f028c3f3f9 · outbound

This paper cites MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 10

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Observation d3542db4-2ef0-4086-b02f-4c7ddc92de71 · outbound

This paper cites Huang, Manu Ramesh, Tamara Berg, and Erik Learned-Miller.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models Huang, Manu Ramesh, Tamara Berg, and Erik Learned-Miller

Reference 11

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Observation 9ada223b-a3e0-485d-8049-e382125cd3ef · outbound

This paper cites Instahide: Instance-hiding schemes for private distributed learning.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models Instahide: Instance-hiding schemes for private distributed learning

Reference 12

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This paper cites Comparing the visual representations and performance of humans and deep neural networks.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models Comparing the visual representations and performance of humans and deep neural networks

Reference 13

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Observation 6718430a-bb59-4c79-b7b0-9110ffcf31ad · outbound

This paper cites Privacy-preserving face recognition with learn- able privacy budgets in frequency domain.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models Privacy-preserving face recognition with learn- able privacy budgets in frequency domain

Reference 14

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This paper cites Efficient and privacy-preserving distributed face recogni- tion scheme via facenet.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models Efficient and privacy-preserving distributed face recogni- tion scheme via facenet

Reference 15

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Observation e80758fc-f68a-4c97-a1f2-30a280c7a6cb · outbound

This paper cites Toward a privacy-preserving face recog- nition system: A survey of leakages and solutions.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models Toward a privacy-preserving face recog- nition system: A survey of leakages and solutions

Reference 16

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Observation 99f26486-c8dd-4ea7-afc0-0817544155d7 · outbound

This paper cites Transferable Adversarial Facial Images for Privacy Protection.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models Transferable Adversarial Facial Images for Privacy Protection

Reference 17

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Observation 653cd140-4f09-4e0b-bb8f-1d5fcae77527 · outbound

This paper cites Il- lumination invariant face recognition using near-infrared im- ages.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models Il- lumination invariant face recognition using near-infrared im- ages

Reference 18

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Observation f3166446-eb03-46f7-9c33-ca45cb8fb862 · outbound

This paper cites Privacy- preserving lightweight face recognition.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models Privacy- preserving lightweight face recognition

Reference 19

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Observation d0568e7b-72cc-473d-8cc5-b7a819bb6363 · outbound

This paper cites Deep learning face attributes in the wild.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models Deep learning face attributes in the wild

Reference 20

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Observation 80c69965-6eee-4f33-a5c2-c738d94aa777 · outbound

This paper cites Lightweight privacy-preserving ensemble classification for face recognition.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models Lightweight privacy-preserving ensemble classification for face recognition

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:08:13.046555Z

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Observation 85997335-7b04-4775-ba72-caf000689b28 · outbound

This paper cites On the reconstruction of face images from deep face templates.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models On the reconstruction of face images from deep face templates

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:08:13.032014Z

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Observation e6d8d10e-c2d3-4fbb-9d5b-480347bdd527 · outbound

This paper cites A privacy-preserving deep learning approach for face recognition with edge computing.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models A privacy-preserving deep learning approach for face recognition with edge computing

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:08:13.015779Z

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This paper cites Scheirer, Arun Ross, Peter Peer, and Vitomir ˇStruc.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models Scheirer, Arun Ross, Peter Peer, and Vitomir ˇStruc

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:08:12.998246Z

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Observation 2da661d2-bf80-4ace-bc14-99580249e8c8 · outbound

This paper cites An overview of privacy-enhancing technologies in biometric recognition.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models An overview of privacy-enhancing technologies in biometric recognition

Reference 25

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Observation 7f4a19e3-a82a-483e-9f1e-29349218d81c · outbound

This paper cites Duetface: Collab- orative privacy-preserving face recognition via channel split- ting in the frequency domain.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models Duetface: Collab- orative privacy-preserving face recognition via channel split- ting in the frequency domain

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:08:12.967341Z

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Observation dc03c0d7-89f8-411f-b94d-72f36f09d013 · outbound

This paper cites Privacy- preserving face recognition using random frequency compo- nents.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models Privacy- preserving face recognition using random frequency compo- nents

Reference 27

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Observation fca88736-6474-4a83-8395-45de6b35ded8 · outbound

This paper cites Privacy-preserving face recognition us- ing trainable feature subtraction.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models Privacy-preserving face recognition us- ing trainable feature subtraction

Reference 28

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Observation fe0c597f-1854-4bf8-b2b8-f62198b6bcd3 · outbound

This paper cites Gender privacy: An ensemble of semi adversarial networks for con- founding arbitrary gender classifiers.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models Gender privacy: An ensemble of semi adversarial networks for con- founding arbitrary gender classifiers

Reference 29

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Observation aa33a016-5b38-405c-92ed-aea1d7572510 · outbound

This paper cites Agedb: the first manually collected, in-the-wild age database.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models Agedb: the first manually collected, in-the-wild age database

Reference 30

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Observation 864efa16-9063-4550-bec4-d1d733494dc6 · outbound

This paper cites Black-box face recovery from identity features.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models Black-box face recovery from identity features

Reference 31

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Observation bf8507c1-b626-4c6f-8a0e-d3c541c9c1db · outbound

This paper cites A meta-analysis and review of holistic face processing.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models A meta-analysis and review of holistic face processing

Reference 32

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Observation 5a562af2-125a-4fb5-af3c-def5cabe45e2 · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models U-net: Convolutional networks for biomedical image segmentation

Reference 33

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Observation 9a2e5faa-3ada-4866-ab49-c926f2667785 · outbound

This paper cites Facenet: A unified embedding for face recognition and clus- tering.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models Facenet: A unified embedding for face recognition and clus- tering

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:08:12.854287Z

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Observation a17ff57f-bb18-41b5-8b57-dfcdb70b5fdc · outbound

This paper cites Ad- ditive margin softmax for face verification.IEEE Signal Pro- cessing Letters, 25(7):926–930, 2018.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models Ad- ditive margin softmax for face verification.IEEE Signal Pro- cessing Letters, 25(7):926–930, 2018

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:08:12.839929Z

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Observation ee90146a-e737-41c1-97ae-493c2c81ffe2 · outbound

This paper cites Privacy-preserving face recognition in the frequency domain.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models Privacy-preserving face recognition in the frequency domain

Reference 36

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Observation db48b702-6fef-40ad-8b1e-f46da95d057a · outbound

This paper cites Privacy-preserving adversarial facial features.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models Privacy-preserving adversarial facial features

Reference 37

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Observation de46e4c5-3316-4d7a-8f86-646da47779b4 · outbound

This paper cites A review of homomorphic encryption for privacy- preserving biometrics.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models A review of homomorphic encryption for privacy- preserving biometrics

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:08:12.792398Z

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Observation 20c415c9-49f3-4a7d-88c6-98dab26493d1 · outbound

This paper cites Efficient and privacy-preserving online face recog- nition over encrypted outsourced data.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models Efficient and privacy-preserving online face recog- nition over encrypted outsourced data

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:08:12.777225Z

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Observation 95cfb4f2-0812-4b76-988a-92320c91258a · outbound

This paper cites Pro-face: A generic framework for privacy- preserving recognizable obfuscation of face images.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models Pro-face: A generic framework for privacy- preserving recognizable obfuscation of face images

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:08:12.761395Z

Source-reported events for the cited work

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Observation a180a3db-1e56-4f9d-9cee-6f67cad49142 · outbound

This paper cites A privacy-preserving multi-task learning framework for face detection, landmark localization, pose estimation, and gender recognition.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models A privacy-preserving multi-task learning framework for face detection, landmark localization, pose estimation, and gender recognition

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:08:12.746004Z

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Observation 31eea4f9-9413-48a1-b87a-cb9b2bf6dff3 · outbound

This paper cites Cross-pose lfw: A database for studying cross-pose face recognition in un- constrained environments.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models Cross-pose lfw: A database for studying cross-pose face recognition in un- constrained environments

Reference 42

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Observation 72d468b8-4b2f-47a5-a116-89a9dad22f72 · outbound

This paper cites Cross-Age LFW: A Database for Studying Cross-Age Face Recognition in Unconstrained Environments.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models Cross-Age LFW: A Database for Studying Cross-Age Face Recognition in Unconstrained Environments

Reference 43

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Observation b6e72647-d7d5-4b48-b0ed-9864e801e734 · outbound

This paper cites Inverting face embeddings with convolutional neural networks.

Local Features Meet Stochastic Anonymization: Revolutionizing Privacy-Preserving Face Recognition for Black-Box Models Inverting face embeddings with convolutional neural networks

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-11T18:08:12.611161Z

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