adVAE

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Implementation of 'Self-Adversarial Variational Autoencoder with Gaussian Anomaly Prior Distribution for Anomaly Detection'

adVAE 최신버젼 다운로드

최종 버전 다운로드 (.zip)

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adVAE (Self-Adversarial Variational Autoencoder)
=====

Implementation of 'Self-Adversarial Variational Autoencoder with Gaussian Anomaly Prior Distribution for Anomaly Detection' (adVAE) [<a href="https://github.com/YeongHyeon/CVAE-AnomalyDetection">Related repository</a>].  
The official implementation is provided by <a href="https://github.com/WangXuhongCN/adVAE">WangXuhongCN</a>.

## Architecture
<div align="center">
  <img src="./figures/advae.png" width="500">  
  <p>Simplified adVAE architecture.</p>
</div>

## Graph in TensorBoard
<div align="center">
  <img src="./figures/graph.png" width="800">  
  <p>Graph of adVAE.</p>
</div>

## Results
<div align="center">
  <img src="./figures/restoring.png" width="800">  
  <p>Restoration result by adVAE.</p>
</div>

<div align="center">
  <img src="./figures/test-box.png" width="350"><img src="./figures/histogram-test.png" width="390">
  <p>Box plot and histogram of restoration loss in test procedure.</p>
</div>

<div align="center">
  <img src="./figures/test-latent_z.png" width="350"><img src="./figures/test-latent_z_T.png" width="350">
  <p>Normal latent space, and transformed latent space (regared as abnormal).</p>
</div>

## Environment
* Python 3.7.4  
* Tensorflow 1.14.0  
* Numpy 1.17.1  
* Matplotlib 3.1.1  
* Scikit Learn (sklearn) 0.21.3

## Reference
[1] Xuhong Wang, et al. (2019). <a href="https://arxiv.org/abs/1903.00904">Self-adversarial Variational Autoencoder with Gaussian Anomaly Prior Distribution for Anomaly Detection.</a>. arXiv preprint arXiv:1903.00904.

adVAE

adVAE 최신버젼 다운로드

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