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paper_code_review

제가 직접 꼼꼼히 읽은 논문과, 이를 구현한 코드를 정리하는 repo입니다.

주로 이미 유명하게 잘 알려진 논문들을 정리할 예정이며, 추가로 제가 연구하고 있는 분야의 논문들도 정리해볼 예정에 있습니다.


  1. Generative Adversarial Nets(GAN)(2014)

    paper review / code review

  2. Auto-Encoding Variational Bayes(VAE)(2013)

    paper review / code review

  3. Adversarial Autoencoders(AAE)(2015)

    paper review / code review

  4. Unsupervised Representation Learning With Deep Convolutional Generative Adversarial Networks (DCGAN)(2015)

    paper review / code review

  5. Wasserstein GAN (WGAN)(2017)

    paper review / code review

  6. Deep Residual Learning for Image Recognition(ResNet)(2015)

    paper review / code review

  7. Wide Residual Networks(WRN)(2016)

    paper review / code review

  8. Learning Deep Features for Discriminative Localization(CAM)(2016)

    paper review / code review

  9. Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization(Grad-CAM)(2017)

    paper review / code review

  10. Patch SVDD: Patch-level SVDD for Anomaly Detection and Segmentation(Patch SVDD)(2020)

    paper review / code review

  11. PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localization(2020)

    paper review / code review

  12. MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications(MobileNetV1)(2017)

    paper review

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