Corpus ID: 220363410

Can Un-trained Neural Networks Compete with Trained Neural Networks at Image Reconstruction?

@article{Darestani2020CanUN,
  title={Can Un-trained Neural Networks Compete with Trained Neural Networks at Image Reconstruction?},
  author={Mohammad Zalbagi Darestani and Reinhard Heckel},
  journal={ArXiv},
  year={2020},
  volume={abs/2007.02471}
}
Convolutional Neural Networks (CNNs) are highly effective for image reconstruction problems. Typically, CNNs are trained on large amounts of training images. Recently, however, un-trained neural networks such as the Deep Image Prior and Deep Decoder have achieved excellent image reconstruction performance for standard image reconstruction problems such as image denoising and image inpainting, without using any training data. This success raises the question whether un-trained neural networks… Expand
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