Skip to content
master
Switch branches/tags
Code

Latest commit

 

Git stats

Files

Permalink
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time
 
 
 
 
 
 
 
 
 
 

LFASR-geometry

PyTorch implementation of AAAI 2020 paper: Learning Light Field Angular Super-Resolution via a Geometry-Aware Network.

[paper]

Requirements

  • Python 3.6
  • PyTorch 1.1
  • 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.

Demo

To produce the results in the paper, run:

python test_pretrained.py --model_path ./pretrained_model/HCI_2x2-7x7.pth   --test_dataset HCI --data_path ./LFData/test_HCI.h5 --angular_out 7 --angular_in 2 --crop 1 --save_img 1

Training

To re-train the model, run:

python train.py --lr 1e-4 --step 500 --epi 1.0 --patch_size 96 --num_cp 10   --layer_num 4  --angular_out 7 --angular_in 2 --dataset HCI --dataset_path ./LFData/train_HCI.h5

About

Repository for "Learning Light Field Angular Super-Resolution via a Geometry-Aware Network", AAAI 2020

Resources

Releases

No releases published

Packages

No packages published