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stpan's Introduction

STPAN: Learning spatial and spatio-temporal pixel aggregations for image and video denoising

This is a official implementation of the paper Learning Spatial and Spatio-Temporal Pixel Aggregations for Image and Video Denoising, TIP 2020.

An earlier arXiv paper: Learning Deformable Kernels for Image and Video Denoising, 2019.

The pytorch implementation is still under preparation and will be released soon.

Please see tf branch for original implementation and models.

Thanks to z-bingo for re-implementing our method in https://github.com/z-bingo/Deformable-Kernels-For-Video-Denoising.git

TODOs

  • Release SPAN and PAN code
  • Release Test and Training Scripts
  • Release Datasets
  • Release Video Denoise models
  • Release Image Denoise models

Installation

For environment setting up:

pip install -r requirement.txt

Dataset Preparation

Training

Testing

Citation

If you find this repo helpful in your research, please cite our paper.

@article{stpan,
  title={Learning spatial and spatio-temporal pixel aggregations for image and video denoising},
  author={Xu, Xiangyu and Li, Muchen and Sun, Wenxiu and Yang, Ming-Hsuan},
  journal={IEEE Transactions on Image Processing},
  year={2020}
}
@article{dcn_denoise,
  title={Learning deformable kernels for image and video denoising},
  author={Xu, Xiangyu and Li, Muchen and Sun, Wenxiu},
  journal={arXiv preprint arXiv:1904.06903},
  year={2019}
}

Contact: [email protected]

stpan's People

Contributors

jojo23333 avatar xuxy09 avatar

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stpan's Issues

[REQ] add a (GH-compliant) license file

Hi there, 1st of all thanks for this awesome work !

Since we've 'doxed' it in our HyMPS project (under VIDEO section \ AI-based page \ Denoisers), can you please add a GH-compliant license file for it ?

As you know, expliciting licensing terms is extremely important to let anyone better/faster understand how to reuse/adapt/modify sources (and not only) in other open projects and vice-versa.

Although it may sounds like a minor aspect, license file omission obviously causes an inconsistent generation of the relative badge too:


(badge-generator URL: https://badgen.net/github/license/jojo23333/STPAN)

You can easily set a standardized one through the GH's license wizard tool.

Last but not least, let us know how we could improve - in your opinion - our categorizations and links to resources in order to favor collaboration between developers (and therefore evolution) of listed projects.

Hope that helps/inspires !

Something wrong.

When I tried to running the code train_multi_gpu.py, I encounter the following error message:

tensorflow.python.framework.errors_impl.InvalidArgumentError: assertion failed: [height must be >= target + offset.]

I don't know whether it is caused by the environmental setting,my environment:Windows 10, python 3.6.5, tensorflow 1.9.0.

By the way, there is an error in line 97 of train_multi_gpu.py, maybe it is "model = stpan".

I look forward that you could complete the codes, environment, and corresponding data set as soon as possible.

Thanks.

file missed

in trainDenoising.py , line 9

File "/content/STPAN/trainDenoising.py", line 9, from fvcore.nn.precise_bn import get_bn_modules, update_bn_stats
but this file is not available in your code ...

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