Skip to content

The source code of ECCV16 'Deep Joint Image Filtering'.

License

MIT, Unknown licenses found

Licenses found

MIT
LICENSE.txt
Unknown
COPYING
Notifications You must be signed in to change notification settings

Yijunmaverick/DeepJointFilter

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

68 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

MatConvNet implementation of our ECCV16 paper on joint image filtering.

Prerequisites

  • Tested on Linux or Windows
  • Matlab R2015b
  • MatConvNet
> matlab/vl_setupnn.m
> matlab/vl_compilenn.m

Training:

Generate the training data (nearly the same way used in SRCNN).

> examples/Train/generate_trainingdata.m

Or please download the training data (for 8x depth upsampling) and put it under the examples/Train/TrainingData/ folder.

> examples/Train/demo_train.m

Testing:

We provide our models for two tasks, i.e., depth map upsampling and Flash/Non-flash image noise reduction.

> examples/Test/cnn_test_upsampling.m
> examples/Test/cnn_test_noise_reduction.m

Note

For training with GPU, please uncomment line 215-217 and 222-223 in matlab/simplenn.m and then re-compile.

> vl_setupnn.m
> vl_compilenn('enableGpu', true)

Citation

@inproceedings{DJF-ECCV-2016,
    author = {Li, Yijun and Huang, Jia-Bin and Ahuja Narendra and Yang, Ming-Hsuan},
    title = {Deep Joint Image Filtering},
    booktitle = {European Conference on Computer Vision},
    year = {2016}
}

Acknowledgement

We express gratitudes to SRCNN as we benefit a lot from both their paper and codes.

About

The source code of ECCV16 'Deep Joint Image Filtering'.

Resources

License

MIT, Unknown licenses found

Licenses found

MIT
LICENSE.txt
Unknown
COPYING

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published