Synthetic Face Recognition
5 papers with code • 5 benchmarks • 3 datasets
Benchmarks
These leaderboards are used to track progress in Synthetic Face Recognition
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LFW
CALFW
Most implemented papers
SynthDistill: Face Recognition with Knowledge Distillation from Synthetic Data
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.
DigiFace-1M: 1 Million Digital Face Images for Face Recognition
Such models are trained on large-scale datasets that contain millions of real human face images collected from the internet.
DCFace: Synthetic Face Generation with Dual Condition Diffusion Model
mk-minchul/dcface
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CVPR 2023
Our 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.
Identity-driven Three-Player Generative Adversarial Network for Synthetic-based Face Recognition
We 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.
IDiff-Face: Synthetic-based Face Recognition through Fizzy Identity-Conditioned Diffusion Models
The availability of large-scale authentic face databases has been crucial to the significant advances made in face recognition research over the past decade.
