Corpus ID: 221370646

Same Same But DifferNet: Semi-Supervised Defect Detection with Normalizing Flows

@article{Rudolph2020SameSB,
  title={Same Same But DifferNet: Semi-Supervised Defect Detection with Normalizing Flows},
  author={M. Rudolph and B. Wandt and B. Rosenhahn},
  journal={ArXiv},
  year={2020},
  volume={abs/2008.12577}
}

• M. Rudolph, B. Wandt, B. Rosenhahn
• Published 2020
• Computer Science, Engineering
• ArXiv

The detection of manufacturing errors is crucial in fabrication processes to ensure product quality and safety standards. Since many defects occur very rarely and their characteristics are mostly unknown a priori, their detection is still an open research question. To this end, we propose DifferNet: It leverages the descriptiveness of features extracted by convolutional neural networks to estimate their density using normalizing flows. Normalizing flows are well-suited to deal with low… Expand

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