VESPCN-PyTorch

PyTorch implementation of ESPCN [1]/VESPCN [2].

How to run the code

Add your own template in template.py, indicating parameters related to running the code (especially, specify the task (Image/MC/Video) and set training/test dataset directories specific to your filesystem)
Add your model in ./model/ directory (filename should be in lower cases)
Type "python3 main.py --template $(your template) --model $(model you want to train)" for training
If you want to add additional options for test benchmark datasets, modify ./data/init.py.
For additional details, refer to [3] (We have borrowed most of the implementation details from there).

[1] W. Shi et al, “Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network,” IEEE CVPR 2016.

[2] J. Caballero et al, “Real-Time Video Super-Resolution with Spatio-Temporal Networks and Motion Compensation,” IEEE CVPR 2017.

Name		Name	Last commit message	Last commit date
Latest commit History 107 Commits
data		data
logger		logger
model		model
tools		tools
.gitignore		.gitignore
README.md		README.md
approx_huber_loss.py		approx_huber_loss.py
main.py		main.py
option.py		option.py
template.py		template.py
test.py		test.py
trainer.py		trainer.py
trainer_mc.py		trainer_mc.py
trainer_vsr.py		trainer_vsr.py
utils.py		utils.py