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Paper Citation Record · LEDGER

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations

As of 17 August 2026, this Paper Citation Record lists 64 of 64 outbound references and 0 inbound Pith citation observations for arXiv:2412.02479.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2412.02479 v2

Coverage vector

measured 64 of 64 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T23:31:19.234765Z

measured 64 of 64 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

64 of 64 outbound references displayed

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  • verified fuzzy46
  • unresolved16
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1918788d-2a77-4931-bc1e-0bf9036f8bdd · outbound

This paper cites GPT-4 Technical Report.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations GPT-4 Technical Report

Reference 1

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Source-reported events for the cited work

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Observation fb8ffd35-ca80-425a-8f97-513457ba42db · outbound

This paper cites Face morphing detection in social media content.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Face morphing detection in social media content

Reference 2

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Observation 03ea2d35-3791-4fcc-9d96-233bd0a6c63e · outbound

This paper cites Evaluating the performance of eigenface, fisherface, and local binary pattern histogram- based facial recognition methods under various weather con- ditions.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Evaluating the performance of eigenface, fisherface, and local binary pattern histogram- based facial recognition methods under various weather con- ditions

Reference 3

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Observation 3b89d329-bba3-4fdc-b761-bc0ccc6f9a39 · outbound

This paper cites Imagecorruptions, 2024.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Imagecorruptions, 2024

Reference 4

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Source-reported events for the cited work

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Observation 228f015e-c261-4ce0-8842-8c3d401749a5 · outbound

This paper cites an unresolved cited work.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Unresolved cited work

Reference 5

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Source-reported events for the cited work

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Observation 5db3b498-6009-4759-84d9-5baa7611451b · outbound

This paper cites Elasticface: Elastic margin loss for deep face recognition.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Elasticface: Elastic margin loss for deep face recognition

Reference 6

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Source-reported events for the cited work

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Observation 78ef4f95-8abd-423d-9992-84aa63dfe75e · outbound

This paper cites Vggface2: A dataset for recognising faces across pose and age.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Vggface2: A dataset for recognising faces across pose and age

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 5f109296-8414-41a5-a35d-fc877512c33a · outbound

This paper cites Mo- bilefacenets: Efficient cnns for accurate real-time face verifi- cation on mobile devices.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Mo- bilefacenets: Efficient cnns for accurate real-time face verifi- cation on mobile devices

Reference 8

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 97652d48-271d-4ed0-916b-4d50460d1170 · outbound

This paper cites Transface: Calibrating trans- former training for face recognition from a data-centric per- spective.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Transface: Calibrating trans- former training for face recognition from a data-centric per- spective

Reference 9

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Source-reported events for the cited work

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Observation e8e6bc3c-54ba-4c54-9bb6-3f4eb473fa37 · outbound

This paper cites Topofr: A closer look at topology alignment on face recognition.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Topofr: A closer look at topology alignment on face recognition

Reference 10

Resolution
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Source-reported events for the cited work

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Observation f433029b-f45a-480b-8242-1063d29ab429 · outbound

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

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Arcface: Additive angular margin loss for deep face recognition

Reference 11

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Source-reported events for the cited work

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Observation df0dda57-0727-4f1d-81fa-7fa43f94dd86 · outbound

This paper cites Enhancing drug abuse face recognition: A study on image corruption and restora- tion.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Enhancing drug abuse face recognition: A study on image corruption and restora- tion

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 14c19e4e-24e6-432f-8780-35dc57468abe · outbound

This paper cites Face detection and facial expression recognition system.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Face detection and facial expression recognition system

Reference 13

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 0e20f64c-bc33-4d47-9e56-2358a827f3c8 · outbound

This paper cites Benchmarking robustness of 3d object detection to common corruptions.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Benchmarking robustness of 3d object detection to common corruptions

Reference 14

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation afe733d5-1382-4ce3-b93e-b50dbec5322c · outbound

This paper cites A study of the effect of JPG compression on adversarial images.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations A study of the effect of JPG compression on adversarial images

Reference 15

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 53d4811c-118b-4636-950c-d3ea8d55c2f8 · outbound

This paper cites Wichmann.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Wichmann

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 8abf4f50-57b6-4c1a-9a15-1d35de9b3ce7 · outbound

This paper cites Wichmann, and Wieland Bren- del.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Wichmann, and Wieland Bren- del

Reference 17

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation c23d33a1-88bc-444b-bb2c-7f5bf62394b5 · outbound

This paper cites Goodfellow, Jonathon Shlens, and Christian Szegedy.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Goodfellow, Jonathon Shlens, and Christian Szegedy

Reference 18

Resolution
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Source-reported events for the cited work

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Observation 0cd8ecae-4050-4ae8-bb4d-b83600e002a9 · outbound

This paper cites Ms-celeb-1m: A dataset and benchmark for large-scale face recognition.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Ms-celeb-1m: A dataset and benchmark for large-scale face recognition

Reference 19

Resolution
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Source-reported events for the cited work

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Observation 3cb69f47-128d-4e17-b3d8-5e0abef34998 · outbound

This paper cites Ganspace: Discovering interpretable gan con- trols.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Ganspace: Discovering interpretable gan con- trols

Reference 20

Resolution
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Source-reported events for the cited work

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Observation d20184a3-e171-465b-9f66-1fa648eef67c · outbound

This paper cites Deep residual learning for image recognition.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Deep residual learning for image recognition

Reference 21

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Source-reported events for the cited work

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Observation 227b0b34-be22-42dd-a23b-9f53c0009b6e · outbound

This paper cites Benchmarking Neural Network Robustness to Common Corruptions and Perturbations.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Benchmarking Neural Network Robustness to Common Corruptions and Perturbations

Reference 22

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation ecdb39d8-0ea5-4f20-bf41-0e0f1aa8bb1d · outbound

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

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 23

Resolution
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Source-reported events for the cited work

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Observation 01f2d494-51cf-4e7d-a962-f99cc9485ab7 · outbound

This paper cites Labeled faces in the wild: A database forstudying face recognition in unconstrained environments.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Labeled faces in the wild: A database forstudying face recognition in unconstrained environments

Reference 24

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation a96a9be6-33ae-4d88-bc97-e8302d577177 · outbound

This paper cites Adaface: Quality adaptive margin for face recognition.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Adaface: Quality adaptive margin for face recognition

Reference 25

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 72e952b6-10f0-42f0-b45e-305ea19d6f8b · outbound

This paper cites Pushing the frontiers of unconstrained face detection and recognition: Iarpa janus benchmark a.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Pushing the frontiers of unconstrained face detection and recognition: Iarpa janus benchmark a

Reference 26

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 081137bd-aa64-45d7-b18f-30d9b31914e2 · outbound

This paper cites Beautygan: Instance-level facial makeup transfer with deep generative adversarial network.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Beautygan: Instance-level facial makeup transfer with deep generative adversarial network

Reference 27

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 10e6128c-d91c-430a-af3d-e3e29f3e6c23 · outbound

This paper cites Image-to-image translation via hierarchical style disentanglement.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Image-to-image translation via hierarchical style disentanglement

Reference 28

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation f3e9b19a-09d0-4370-8ea5-ef34f881a817 · outbound

This paper cites Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers

Reference 29

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation b22bbf85-b1d1-45dc-a459-e02e20f8e0c9 · outbound

This paper cites AI-Face: A Million-Scale Demographically Annotated AI-Generated Face Dataset and Fairness Benchmark.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations AI-Face: A Million-Scale Demographically Annotated AI-Generated Face Dataset and Fairness Benchmark

Reference 30

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:31:17.854793Z digest=sha256:8fe0bf87bb69fc3454e12c3cff29f8225f429ed7aa53d9b3af598b4746b9b97c

Observation d15d99d3-4df2-423b-812c-55504e91643f · outbound

This paper cites Diff- bir: Toward blind image restoration with generative diffusion prior.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Diff- bir: Toward blind image restoration with generative diffusion prior

Reference 31

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 01411b54-0270-440d-8d00-2077f6284de3 · outbound

This paper cites A study of face recognition as people age.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations A study of face recognition as people age

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:31:24.040610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 59e667f8-09d8-4a8b-9184-12262559479c · outbound

This paper cites Sphereface: Deep hypersphere embedding for face recognition.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Sphereface: Deep hypersphere embedding for face recognition

Reference 33

Resolution
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no resolver link, observed 2026-08-11T23:31:18.001263Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 081b9e8a-4283-4de8-8b59-9d1c26f978fa · outbound

This paper cites Shufflenet v2: Practical guidelines for efficient cnn architec- ture design.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Shufflenet v2: Practical guidelines for efficient cnn architec- ture design

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:31:23.928245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T23:31:18.034749Z digest=sha256:401b41b15556825fdbcdac6545a6340e53ee1606fb295a7dc4457971fdef9ab9

Observation ff9a99c7-8572-4efe-8185-abd3662eb542 · outbound

This paper cites Towards deep learning models resistant to adversarial attacks.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Towards deep learning models resistant to adversarial attacks

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:31:23.885240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T23:31:18.071471Z digest=sha256:282ab71b5da41433b4dc46f5fbf2dc79969d79041027fc13c70ae4479978a6fa

Observation ecc68d55-86f1-4b17-9dc8-729559e30e50 · outbound

This paper cites Iarpa janus benchmark-c: Face dataset and protocol.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Iarpa janus benchmark-c: Face dataset and protocol

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:31:23.822568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T23:31:18.095838Z digest=sha256:adf6f55621b44b3d7e0db316c4d707901ffd2778cd145699e88a6c42fa16a49a

Observation 2c2850ea-0068-4c32-8f8a-c012a7f3405a · outbound

This paper cites Ecker, Matthias Bethge, and Wieland Brendel.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Ecker, Matthias Bethge, and Wieland Brendel

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:31:23.773773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T23:31:18.129930Z digest=sha256:9c4b324b7247c45a72b49a5098f258151338b7738e5a0eaf20937680276f3b1c

Observation 2366fd64-93e0-4193-b58e-b5bd98361cdb · outbound

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

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Agedb: the first manually collected, in-the-wild age database

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:31:23.694742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T23:31:18.175048Z digest=sha256:e06ae0b7690c1d4c744035d0850a9bb3725780509f1f6fa3543d6cec8b9327db

Observation 6d941c70-d628-4232-8c93-720aea3e2d11 · outbound

This paper cites Beyond masks: On the generalization of masked face recognition models to occluded face recognition.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Beyond masks: On the generalization of masked face recognition models to occluded face recognition

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:31:23.524729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T23:31:18.204993Z digest=sha256:940632831db5e082be8c1c57275aa2a500bd7bf6dea3066784b5448eaa2dede5

Observation 8aa82310-9e25-4f1a-8ba9-d5f4766a80ec · outbound

This paper cites A system- atic review of noise types, denoising methods, and evalua- tion metrics in images.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations A system- atic review of noise types, denoising methods, and evalua- tion metrics in images

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:31:23.344755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T23:31:18.227927Z digest=sha256:bebb89fc2f204ae63d8e327e457a064335b2383d1ade379c6f5fb24eb5d6f38c

Observation 64797e0b-29b4-4f5d-b678-3eef955af372 · outbound

This paper cites Benchmarking and analyzing point cloud classification under corruptions.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Benchmarking and analyzing point cloud classification under corruptions

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:31:23.174730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T23:31:18.254410Z digest=sha256:db51dab225fab67c11e7453db9ad0f36230e77821e0784d3c782aaf23d463dbe

Observation 9bb83d50-62f3-401b-9671-e87c31726c26 · outbound

This paper cites Pivotal tuning for latent-based editing of real im- ages.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Pivotal tuning for latent-based editing of real im- ages

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-11T23:31:18.271710Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:31:18.271710Z digest=sha256:721c084fa80c0bcb6890683448bc66ae7eb52e3f2da94ce1aac69224217c010b

Observation a812aa8e-d9b5-4202-9688-4744d715b06e · outbound

This paper cites Mobilenetv2: Inverted residuals and linear bottlenecks.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Mobilenetv2: Inverted residuals and linear bottlenecks

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:31:22.974756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T23:31:18.331328Z digest=sha256:de162da9be00ca43564546dd30583b9587527696689519a54467ae0d05a1e624

Observation c2e748be-aedf-45f2-828b-fe06a6c6d5e8 · outbound

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

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Facenet: A unified embedding for face recognition and clus- tering

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:31:22.845267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T23:31:18.354827Z digest=sha256:0fff647ae6c84f2b0fb2db2af5be6f710ea28e92232a3d26c688c40981d7f9e9

Observation 1d5a4e3c-c9d7-4278-8eac-b3b88dee83f3 · outbound

This paper cites Frontal to profile face verification in the wild.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Frontal to profile face verification in the wild

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:31:22.679915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T23:31:18.405847Z digest=sha256:13155e4d5cc5c9b2e49d927581dcfd02c62dfd2e8e0816afc8336c9c27341cf5

Observation 1e915d9f-0d98-4f36-9af7-817b032c48f7 · outbound

This paper cites In- 10 triguing properties of neural networks.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations In- 10 triguing properties of neural networks

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:31:22.591673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T23:31:18.425870Z digest=sha256:e9635b562cbde0876f711c7e81024aef44f518b6b4e500b47fb3b04d175964ad

Observation 835f091c-ee3f-4619-b787-800a80ed8364 · outbound

This paper cites Deepface: Closing the gap to human-level perfor- mance in face verification.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Deepface: Closing the gap to human-level perfor- mance in face verification

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:31:22.525752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T23:31:18.475244Z digest=sha256:eb0286014043690d99705e37a2672dcbd054a0ad9d38716e51b989aa0caa4862

Observation a585b90c-3ec2-46b3-8ae9-da26f934f794 · outbound

This paper cites Measuring ro- bustness to natural distribution shifts in image classifica- tion.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Measuring ro- bustness to natural distribution shifts in image classifica- tion

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:31:22.404744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T23:31:18.495320Z digest=sha256:c4bbaaabe67daf93ddde21ccff2272ec63fc0d4b5d36f30c7b2f02880208b2d5

Observation 4226a4fd-cbae-4516-8df4-7398ae26b336 · outbound

This paper cites Ad- ditive margin softmax for face verification.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Ad- ditive margin softmax for face verification

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:31:22.247315Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T23:31:18.534753Z digest=sha256:5b6b8dc8d52fc69e033f6b3d3bd6857cf9e33a5a5df1a0dd3935a396521069dd

Observation 8f0266c6-4360-41a4-8e68-cb4288f03154 · outbound

This paper cites Cosface: Large margin cosine loss for deep face recognition.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Cosface: Large margin cosine loss for deep face recognition

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:31:22.084738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T23:31:18.594760Z digest=sha256:da14b63d304aaa19774d6a111112fb5481153283ef93185b35392ef0241b40f6

Observation c70bed1d-4d5a-43bf-9c1c-77c516cf2063 · outbound

This paper cites To- wards real-world blind face restoration with generative fa- cial prior.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations To- wards real-world blind face restoration with generative fa- cial prior

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-11T23:31:18.628058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:31:18.628058Z digest=sha256:6ea62c6f0eae31524466e7d32e2d5bfab5f218ae06fb78d11e21f65a91992df2

Observation 75ec3236-ea9d-4b04-93fa-b73b9c308116 · outbound

This paper cites Iarpa janus benchmark-b face dataset.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Iarpa janus benchmark-b face dataset

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:31:21.784747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T23:31:18.664759Z digest=sha256:07e40df78cedd32995b9e04f08b7497ec9de35b02145c89a5e4053812fe2eb37

Observation a598989a-38c7-4dbc-b91d-86b84791f156 · outbound

This paper cites Face recognition in unconstrained videos with matched background similarity.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Face recognition in unconstrained videos with matched background similarity

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:31:21.605021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T23:31:18.734797Z digest=sha256:4bd8bee625fac0577d8a1a3dbee948966949181f0d0189f97077a5e1865e14ec

Observation 46c6f937-25a7-4284-958b-d87efd9784d2 · outbound

This paper cites Mitigating Adversarial Effects Through Randomization.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Mitigating Adversarial Effects Through Randomization

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-11T23:31:18.757603Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:31:18.757603Z digest=sha256:44a736a0b3da97346123e7dc64874c3a8cef9092d105e6b0151e3f2cb137c945

Observation 2b6b8d88-87d4-47db-88a7-118618a76491 · outbound

This paper cites Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-11T23:31:18.804757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:31:18.804757Z digest=sha256:6de010848458256cf18f6a4e4fb2d8cc1d5dd792af0d5b7876f1fbdb860b186c

Observation 57891035-2ae7-4c7d-8789-1c77f0d1b0cd · outbound

This paper cites RobFR: Benchmarking Adversarial Robustness on Face Recognition.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations RobFR: Benchmarking Adversarial Robustness on Face Recognition

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-11T23:31:18.864753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:31:18.864753Z digest=sha256:ea5290d0f9d5662760d8589a0a692ed59e99459286993a59051236bb7a866b38

Observation 113d1fcb-1b1e-4243-8737-a3a6c0cf7393 · outbound

This paper cites Theoretically principled trade-off between robustness and accuracy.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Theoretically principled trade-off between robustness and accuracy

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-11T23:31:18.914753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:31:18.914753Z digest=sha256:6595358739393c8e42b73881fb526d3b43252ab05d0c02c987e8bd664052d5e0

Observation a5400b8b-ffc0-4503-ae36-b9362cc0d628 · outbound

This paper cites Joint face detection and alignment using multitask cascaded convolutional networks.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Joint face detection and alignment using multitask cascaded convolutional networks

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:31:21.300511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T23:31:18.964738Z digest=sha256:0a014c68ab20a3f71059a1bf3bb1c9a93f82c5ac9fc680dc5223dea19671bf7d

Observation 9a065450-6bc4-4dfb-88c8-30a9cbc349db · outbound

This paper cites Deep disguised faces recognition.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Deep disguised faces recognition

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:31:21.184726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T23:31:19.014753Z digest=sha256:e8eb23a01fa2836e2fb8b64827cc297895a922611d90022d95a89badcb131b49

Observation 190f4538-5f63-4104-b4c9-f4b50aa12dd6 · outbound

This paper cites Facial expression analysis under partial occlusion: A survey.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Facial expression analysis under partial occlusion: A survey

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:31:21.094742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T23:31:19.047584Z digest=sha256:34607b4d55baa6c76d0fac7c5377a288ba5dd5d1de95423ac7f388e79d817d99

Observation 9c0c9997-abbb-44f5-8d2c-8fe3828ab20f · outbound

This paper cites Shufflenet: An extremely efficient convolutional neural net- work for mobile devices.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Shufflenet: An extremely efficient convolutional neural net- work for mobile devices

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:31:21.012111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T23:31:19.064751Z digest=sha256:b56123e27ec70ce0cb681e15f070c662e40bad8ec123920ba52b340a9d40b556

Observation f508cfaf-7100-47fd-b037-d1ab0db13082 · outbound

This paper cites Torr, and Yi Zhang.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Torr, and Yi Zhang

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:31:20.920869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T23:31:19.125056Z digest=sha256:f842658d0f7aa479d6647895bf626c34ad711b6fab881d5b7e72c64f5f1b90e8

Observation e4576cb0-48b9-4daa-8988-3499d03e061d · outbound

This paper cites Towards robust blind face restora- tion with codebook lookup transformer.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Towards robust blind face restora- tion with codebook lookup transformer

Reference 63

Resolution
malformed identifier
raw_fallback, observed 2026-08-11T23:31:19.809527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T23:31:19.174752Z digest=sha256:f5f1a177d56b1ce3617a4a11f09d7cb023faa93777f5af31e16a2fd9c7ba1a7d

Observation 80e5a121-690b-4785-9c08-75372565228c · outbound

This paper cites Open-source Model Eval.

OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations Open-source Model Eval

Reference 64

Resolution
verified exact
raw_fallback, observed 2026-08-11T23:31:19.584822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T23:31:19.234765Z digest=sha256:9515227812eb5968e55651f581ef6e59165b9799dae966f1fc9065022750aedf

Pith citing papers

No inbound Pith citation observations are available.