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PyTorch implementation of ECCV 2020 paper (Oral): "Deep Spatial-angular Regularization for Compressive Light Field Reconstruction over Coded Apertures".

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LFCA

PyTorch implementation of ECCV 2020 paper (Oral): "Deep Spatial-angular Regularization for Compressive Light Field Reconstruction over Coded Apertures".

Requrements

  • Python 3.7.4
  • PyTorch 1.3.1
  • Matlab (for training/test data generation)

Dataset

We provide MATLAB code for preparing the training and test data. Please first download light field datasets, and put them into corresponding folders in LFData.

Test

We provide the pre-trained model for 2 -> 49 task on Lytro dataset.

To test, run:

python lfca_test.py

Train

To train, run:

python lfca_train.py

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PyTorch implementation of ECCV 2020 paper (Oral): "Deep Spatial-angular Regularization for Compressive Light Field Reconstruction over Coded Apertures".

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