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Parameter and Data-Efficient Spectral StyleDCGAN

arXiv 2404.00597 ↗First posted 31 Mar 2024cs.CVcited by 0

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Abstract (arXiv)

We present a simple, highly parameter, and data-efficient adversarial network for unconditional face generation. Our method: Spectral Style-DCGAN or SSD utilizes only 6.574 million parameters and 4739 dog faces from the Animal Faces HQ (AFHQ) dataset as training samples while preserving fidelity at low resolutions up to 64x64. Code available at https://github.com/Aryan-Garg/StyleDCGAN.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 21 of its 31 references that are in the map. First posted on arXiv 31 Mar 2024.

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21 of 31 references.

References · 21

  1. 2014ImageNet Large Scale Visual Recognition Challengecited by 8,498
  2. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,255
  3. 2018A Style-Based Generator Architecture for Generative Adversarial Networkscited by 6,013
  4. 2022Generative Adversarial Networkscited by 5,627
  5. 2019Analyzing and Improving the Image Quality of StyleGANcited by 3,588
  6. 2015Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networkscited by 2,054
  7. 2017Arbitrary Style Transfer in Real-time with Adaptive Instance Normalizationcited by 2,010
  8. 2018Spectral Normalization for Generative Adversarial Networkscited by 1,636
  9. 2015LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loopcited by 1,355
  10. 2020Training Generative Adversarial Networks with Limited Datacited by 1,186
  11. 2021Alias-Free Generative Adversarial Networkscited by 1,184
  12. 2019StarGAN v2: Diverse Image Synthesis for Multiple Domainscited by 1,098
9 more
  1. 2022Diffusion Models in Vision: A Surveycited by 1,015
  2. 2018Self-Attention Generative Adversarial Networkscited by 809
  3. 2017Towards Principled Methods for Training Generative Adversarial Networkscited by 464
  4. 2020Differentiable Augmentation for Data-Efficient GAN Trainingcited by 363
  5. 2018Generative Adversarial Network in Medical Imaging: A Reviewcited by 257
  6. 2018The relativistic discriminator: a key element missing from standard GANcited by 238
  7. 2021Ensembling Off-the-shelf Models for GAN Trainingcited by 86
  8. 2022A Comprehensive Survey on Data-Efficient GANs in Image Generationcited by 20
  9. 2019Progressive Augmentation of GANscited by 13

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