Paper Citation Record · LEDGER

Enhancing Domain Diversity in Synthetic Data Face Recognition with Dataset Fusion

As of 20 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2507.16790.

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

pith.paper-citation-record.v1
2507.16790 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:04:59.966308Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

34 of 34 outbound references displayed

verified exact2
verified fuzzy28
unresolved4
parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8bdbf901-28dd-46a0-b605-f134d8cfa23b · outbound

This paper cites Digiface-1m: 1 million digi- tal face images for face recognition.

Enhancing Domain Diversity in Synthetic Data Face Recognition with Dataset Fusion Digiface-1m: 1 million digi- tal face images for face recognition

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:00.983299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 22b8e4ac-2c69-4a80-9c20-3c1c5851cca3 · outbound

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

Enhancing Domain Diversity in Synthetic Data Face Recognition with Dataset Fusion Sface: Privacy-friendly and accurate face recognition using synthetic data

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:00.947802Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b153a39c-91d9-47e8-9353-5cc2d5cf2214 · outbound

This paper cites Idiff-face: Synthetic-based face recognition through fizzy identity-conditioned diffusion model.

Enhancing Domain Diversity in Synthetic Data Face Recognition with Dataset Fusion Idiff-face: Synthetic-based face recognition through fizzy identity-conditioned diffusion model

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:00.922732Z

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Observation d6f362bc-605b-41f8-ba5b-eee66ca08fdd · outbound

This paper cites Exfacegan: Exploring identity directions in gan’s learned latent space for synthetic identity generation.

Enhancing Domain Diversity in Synthetic Data Face Recognition with Dataset Fusion Exfacegan: Exploring identity directions in gan’s learned latent space for synthetic identity generation

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:00.896846Z

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Observation a97037c6-838c-493f-8bf1-ad01f2eefbed · outbound

This paper cites Frcsyn challenge at cvpr 2024: Face recog- nition challenge in the era of synthetic data.

Enhancing Domain Diversity in Synthetic Data Face Recognition with Dataset Fusion Frcsyn challenge at cvpr 2024: Face recog- nition challenge in the era of synthetic data

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:00.871719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0172d81d-f931-4308-a837-7456c8bc2439 · outbound

This paper cites Second frcsyn-ongoing: Winning solutions and post- challenge analysis to improve face recognition with synthetic data.

Enhancing Domain Diversity in Synthetic Data Face Recognition with Dataset Fusion Second frcsyn-ongoing: Winning solutions and post- challenge analysis to improve face recognition with synthetic data

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:00.845898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b3f89f72-f5ea-4f89-90aa-7a77794c4355 · outbound

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

Enhancing Domain Diversity in Synthetic Data Face Recognition with Dataset Fusion Arcface: Additive angular margin loss for deep face recognition

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:00.824800Z

Source-reported events for the cited work

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Observation fe34db2f-332a-4d7f-9352-58cfff4c2baa · outbound

This paper cites Disentangled and controllable face image genera- tion via 3d imitative-contrastive learning.

Enhancing Domain Diversity in Synthetic Data Face Recognition with Dataset Fusion Disentangled and controllable face image genera- tion via 3d imitative-contrastive learning

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:00.800390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ec368b40-fb42-4e4b-961d-9ad3b969eb6a · outbound

This paper cites Synthetic Face Datasets Generation via Latent Space Exploration from Brownian Identity Diffusion.

Enhancing Domain Diversity in Synthetic Data Face Recognition with Dataset Fusion Synthetic Face Datasets Generation via Latent Space Exploration from Brownian Identity Diffusion

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-08-06T15:05:00.095228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e93ebb3b-24a5-4f4b-8e07-d24fc497bbd2 · outbound

This paper cites Digi2real: Bridging the realism gap in synthetic data face recognition via foun- dation models.

Enhancing Domain Diversity in Synthetic Data Face Recognition with Dataset Fusion Digi2real: Bridging the realism gap in synthetic data face recognition via foun- dation models

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:00.768286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ae6d8cbe-3e36-4f22-8806-7f3f364c1cb3 · outbound

This paper cites Edgeface: Efficient face recognition model for edge devices.

Enhancing Domain Diversity in Synthetic Data Face Recognition with Dataset Fusion Edgeface: Efficient face recognition model for edge devices

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:00.737249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5fa5087e-8dbe-4893-9df7-b6699461a39d · outbound

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

Enhancing Domain Diversity in Synthetic Data Face Recognition with Dataset Fusion Ms-celeb-1m: A dataset and benchmark for large-scale face recognition

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:00.699562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2b232abf-5abb-494d-94ba-3192269a6118 · outbound

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

Enhancing Domain Diversity in Synthetic Data Face Recognition with Dataset Fusion Labeled faces in the wild: A database forstudying face recognition in unconstrained environments

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:00.672815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6f867724-a557-425d-93e6-2b8a849ac86a · outbound

This paper cites A style-based generator architecture for generative adversarial networks.

Enhancing Domain Diversity in Synthetic Data Face Recognition with Dataset Fusion A style-based generator architecture for generative adversarial networks

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:00.642125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 40d3f9ca-afd0-45fb-8b0a-aa4a680d6024 · outbound

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

Enhancing Domain Diversity in Synthetic Data Face Recognition with Dataset Fusion Adaface: Quality adaptive margin for face recognition

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:00.611766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e148b656-6d13-4c72-97c3-021a3d8cd858 · outbound

This paper cites Identity-driven three- player generative adversarial network for synthetic-based face recognition.

Enhancing Domain Diversity in Synthetic Data Face Recognition with Dataset Fusion Identity-driven three- player generative adversarial network for synthetic-based face recognition

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:00.586826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ed5f80d0-fe0c-4a6d-92c1-5c6ccd096f53 · outbound

This paper cites Gandiffface: Controllable generation of synthetic datasets for face recognition with realistic varia- tions.

Enhancing Domain Diversity in Synthetic Data Face Recognition with Dataset Fusion Gandiffface: Controllable generation of synthetic datasets for face recognition with realistic varia- tions

Reference 17

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Source-reported events for the cited work

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Observation eedb7acf-1098-4db6-abe7-4f976faf53fa · outbound

This paper cites Frcsyn challenge at wacv 2024: Face recognition challenge in the era of synthetic data.

Enhancing Domain Diversity in Synthetic Data Face Recognition with Dataset Fusion Frcsyn challenge at wacv 2024: Face recognition challenge in the era of synthetic data

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:00.543437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation db66892b-ec00-4b47-b660-9fcbb6732106 · outbound

This paper cites Frcsyn-ongoing: Benchmarking and comprehensive evaluation of real and synthetic data to im- prove face recognition systems.

Enhancing Domain Diversity in Synthetic Data Face Recognition with Dataset Fusion Frcsyn-ongoing: Benchmarking and comprehensive evaluation of real and synthetic data to im- prove face recognition systems

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:00.502805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e9fd4453-7d06-4fbb-a694-fd56cad05dd7 · outbound

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

Enhancing Domain Diversity in Synthetic Data Face Recognition with Dataset Fusion Agedb: the first manually collected, in-the-wild age database

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:00.473632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 36084ced-a7e6-475c-8cc5-a1ea9eda7c9b · outbound

This paper cites Arc2face: A foundation model for id-consistent human faces.

Enhancing Domain Diversity in Synthetic Data Face Recognition with Dataset Fusion Arc2face: A foundation model for id-consistent human faces

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:00.441510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7075e249-67fa-4159-a33a-febe8dd92c3a · outbound

This paper cites Synface: Face recognition with syn- thetic data.

Enhancing Domain Diversity in Synthetic Data Face Recognition with Dataset Fusion Synface: Face recognition with syn- thetic data

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:00.417550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e4bb1aa8-9902-446f-858b-acac815c2335 · outbound

This paper cites Learning transferable visual models from natural language supervi- sion.

Enhancing Domain Diversity in Synthetic Data Face Recognition with Dataset Fusion Learning transferable visual models from natural language supervi- sion

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T15:04:59.890419Z

Source-reported events for the cited work

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Observation 440a6275-cb0b-435a-a9fc-7981aebfe29e · outbound

This paper cites Synthetic to Authentic: Transferring Realism to 3D Face Renderings for Boosting Face Recognition.

Enhancing Domain Diversity in Synthetic Data Face Recognition with Dataset Fusion Synthetic to Authentic: Transferring Realism to 3D Face Renderings for Boosting Face Recognition

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-08-06T15:05:00.065865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c20ca598-56a8-4784-b699-563962505b57 · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

Enhancing Domain Diversity in Synthetic Data Face Recognition with Dataset Fusion High-resolution image synthesis with latent diffusion models

Reference 25

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Source-reported events for the cited work

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Observation 616ac9f2-a618-4e54-a52c-d6b724d640f6 · outbound

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

Enhancing Domain Diversity in Synthetic Data Face Recognition with Dataset Fusion Frontal to profile face verification in the wild

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:00.331984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation feeea045-43f1-4e3b-a3ee-49d75cd0de8f · outbound

This paper cites Synthdistill: Face recognition with knowledge distilla- tion from synthetic data.

Enhancing Domain Diversity in Synthetic Data Face Recognition with Dataset Fusion Synthdistill: Face recognition with knowledge distilla- tion from synthetic data

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:00.304418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4964528f-e722-40bc-9059-b5299ee10152 · outbound

This paper cites Sdfr: Synthetic data for face recognition competition.

Enhancing Domain Diversity in Synthetic Data Face Recognition with Dataset Fusion Sdfr: Synthetic data for face recognition competition

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:00.280371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0a4bb0b7-4ed3-454a-8794-18de766fabc5 · outbound

This paper cites Knowledge distillation for face recognition using syn- thetic data with dynamic latent sampling.

Enhancing Domain Diversity in Synthetic Data Face Recognition with Dataset Fusion Knowledge distillation for face recognition using syn- thetic data with dynamic latent sampling

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:00.245165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5d950ca5-8804-452d-a124-2774d9fcde7d · outbound

This paper cites Fake it till you make it: face analysis in the wild using synthetic data alone.

Enhancing Domain Diversity in Synthetic Data Face Recognition with Dataset Fusion Fake it till you make it: face analysis in the wild using synthetic data alone

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:00.215488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9ffbcd13-e243-4df7-9f07-cc8e1882be83 · outbound

This paper cites Vec2face: Scaling face dataset generation with loosely constrained vectors.

Enhancing Domain Diversity in Synthetic Data Face Recognition with Dataset Fusion Vec2face: Scaling face dataset generation with loosely constrained vectors

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:00.180098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7b1bace0-774f-4bfb-970e-565b8edb06f6 · outbound

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

Enhancing Domain Diversity in Synthetic Data Face Recognition with Dataset Fusion Cross-pose lfw: A database for studying cross-pose face recognition in un- constrained environments

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:00.153555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c53a6ee5-a1d5-4921-923a-b9180b6b150e · outbound

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

Enhancing Domain Diversity in Synthetic Data Face Recognition with Dataset Fusion Cross-Age LFW: A Database for Studying Cross-Age Face Recognition in Unconstrained Environments

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-06T15:04:59.958807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9f26b924-f180-453e-9685-0fdde32c0acf · outbound

This paper cites Webface260m: A benchmark unveiling the power of million-scale deep face recognition.

Enhancing Domain Diversity in Synthetic Data Face Recognition with Dataset Fusion Webface260m: A benchmark unveiling the power of million-scale deep face recognition

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:00.122179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

No inbound Pith citation observations are available.