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Using Augmented Face Images to Improve Facial Recognition Tasks

arXiv 2205.06873 ↗First posted 13 May 2022cs.CV cs.GRcited by 0

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Abstract (arXiv)

We present a framework that uses GAN-augmented images to complement certain specific attributes, usually underrepresented, for machine learning model training. This allows us to improve inference quality over those attributes for the facial recognition tasks.

Key facts. No citing papers in the map yet (data through 13 Oct 2026). Builds on 7 of its 16 references that are in the map. First posted on arXiv 13 May 2022.

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References · 7

  1. 2014Adam: A Method for Stochastic Optimizationcited by 37,093
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  3. 2016Image-to-Image Translation with Conditional Adversarial Networkscited by 4,516
  4. 2019Analyzing and Improving the Image Quality of StyleGANcited by 3,585
  5. 2019Interpreting the Latent Space of GANs for Semantic Face Editingcited by 692
  6. 2021Designing an Encoder for StyleGAN Image Manipulationcited by 542
  7. 2021Fake It Till You Make It: Face analysis in the wild using synthetic data alonecited by 200

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