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Final Project for DD2412 Deep Learning Advance Course, NIPS19-reproducibility challenge

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Final project DD2412

This is final project from the course DD2412-Deep Learning, Advanced project.

In this project we reproduce the experiments and conducted a study from the paper:

  • Zongsheng Yue, Hongwei Yong, Qian Zhao, Lei Zhang, and Deyu Meng. Variational denoising network: Toward blind noise modeling and removal. (NeurIPS, 2019) arXiv

Find our report here: report

Requirements:

  • Python 3.7.*
  • Pytorch 1.2.0

How to run:

Training:

For simulated noise:

python simulation_training.py

For benchmark train:

  • First obtain the training and validation data files by running:
python datasets/train_data_sidd.py
python datasets/validation_data_sidd.py
  • Then train by running:
python benchmark_training.py

this file performs training and validation

Testing

For testing the simulation train:

python Testing_simulation.py

Authors:

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Final Project for DD2412 Deep Learning Advance Course, NIPS19-reproducibility challenge

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