Code for the paper "Geometry-guided Compact Compression for Light Field Image using Graph Convolutional Networks"
'train.py' is used to train the GCC, it generate the pt model file.
'test.py' is used to run the forward network of the model, which can reconstruct the image of the light field.
'model.py' is the concrete structure of the network.
'util.py' contains a preprocessor function for the light field data set, graph modeling function, performance evaluation function.
The datasets used in the article is available from:
http://plenodb.jpeg.org/lf/epfl
https://lightfield-analysis.uni-konstanz.de/
This section of code was tested on ubuntu20.04 and RTX 2080 ti.
The HEVC compressed version is HM-16.20.
Select the DGL version corresponding to cuda.
Please change the file path of the dataset in code.