Browse State-of-the-Art › Synthetic Face Recognition
Synthetic Face Recognition
7 papers with code · 5 benchmarks · 3 datasets archive 2025-07-28
Benchmarks archive 2025-07-28
5 leaderboard tables shown for this task, 5 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.
| Dataset | Best model (first row in archive order) | Paper | Code | Syntology | Compare |
|---|---|---|---|---|---|
| AgeDB-30 (3 rows) | SynthDistill | SynthDistill: Face Recognition with Knowledge Distillation from... | code | Syntology ran 1 of 1 samples · 0 unverified | Compare |
| CALFW (3 rows) | SynthDistill | SynthDistill: Face Recognition with Knowledge Distillation from... | code | Syntology ran 1 of 1 samples · 0 unverified | Compare |
| CFP-FP (3 rows) | SynthDistill | SynthDistill: Face Recognition with Knowledge Distillation from... | code | Syntology ran 1 of 1 samples · 0 unverified | Compare |
| CPLFW (3 rows) | SynthDistill | SynthDistill: Face Recognition with Knowledge Distillation from... | code | Syntology ran 1 of 1 samples · 0 unverified | Compare |
| LFW (3 rows) | SynthDistill | SynthDistill: Face Recognition with Knowledge Distillation from... | code | Syntology ran 1 of 1 samples · 0 unverified | Compare |
Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
3 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
No subtask under this task in the archive's task tree.
Parent tasks archive 2025-07-28
Most implemented papers archive 2025-07-28
7 shown of 7 papers with code (12 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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16 Apr 2024 2 repositories listedSynthetic data is gaining increasing relevance for training machine learning models.
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28 Aug 2023 2 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)While generating synthetic datasets for training face recognition models is an alternative option, it is challenging to generate synthetic data with sufficient intra-class variations.
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30 Apr 2023 2 repositories listedWe empirically proved that our IDnet synthetic images are of higher identity discrimination in comparison to the conventional two-player GAN, while maintaining a realistic intra-identity variation.
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27 Feb 2025 1 repository listedWhile existing synthetic-based face recognition methods have made significant progress in generating identity-preserving images, they are severely plagued by context overfitting, resulting in a lack of intra-class…
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9 Aug 2023 1 repository listed Syntology ran 19 of 21 samples · 2 unverified · 21 pointer-only (licence)The availability of large-scale authentic face databases has been crucial to the significant advances made in face recognition research over the past decade.
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14 Apr 2023 1 repository listedOur novel Patch-wise style extractor and Time-step dependent ID loss enables DCFace to consistently produce face images of the same subject under different styles with precise control.
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5 Oct 2022 1 repository listedSuch models are trained on large-scale datasets that contain millions of real human face images collected from the internet.
Syntology lines on 2 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
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