Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-11T23:31:19.234765Z
Paper Citation Record · LEDGER
OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations
As of 16 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.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
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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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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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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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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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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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
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Source-reported events for the cited work
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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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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
- Resolution
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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
- Resolution
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Source-reported events for the cited work
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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
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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
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Source-reported events for the cited work
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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
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Observation 53d4811c-118b-4636-950c-d3ea8d55c2f8 · outbound
This paper cites Wichmann.
Reference 16
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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
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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
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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
- Resolution
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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
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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
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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
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Source-reported events for the cited work
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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
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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
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Source-reported events for the cited work
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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
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Source-reported events for the cited work
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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
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Source-reported events for the cited work
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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
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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
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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
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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
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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
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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
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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
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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
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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
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Source-reported events for the cited work
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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
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Source-reported events for the cited work
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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
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Source-reported events for the cited work
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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
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Source-reported events for the cited work
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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
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Source-reported events for the cited work
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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
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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
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Source-reported events for the cited work
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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
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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.
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
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Source-reported events for the cited work
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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
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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.
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
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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.
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
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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.
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
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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.
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
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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.
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
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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.
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.
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
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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.
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
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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.
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.
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.
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.
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.
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
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- 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.
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.
Pith citing papers
No inbound Pith citation observations are available.