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Compression and Denoising of Transient Light Transport

teaser

General Information

  • Accepted: SIGGRAPH 2019 Posters; Optics Letters
  • Writers: Yun Liang, Mingqin Chen, Zesheng Huang, Diego Gutierrez, Adolfo Muñoz, Julio Marco
  • Institute: South China Agricultural University; Universidad de Zaragoza

For more information please see the paper:

Requirements

  • Python 3.6
  • Tensorflow 1.12.0(https://www.tensorflow.org)
  • numpy
  • scipy
  • h5py All of them can be installed via conda (anaconda), e.g.
conda install scikit-image

How to Execute Demo

We have written a demo code in reconstruction.py. In the main function of it, there called two different functions:

  • demo_recon_video() : this function demonstrates our reconstruction for the transient image "church_albedo_1_view_2.h5".
  • demo_recon_anydata(): this function demonstrates our reconstruction for any data.

How to Train the Network

  • Set the value of N_FILE_SAMPE in params.py, which means how many sample(1 x 4096 x 9 x 9 x 1) in one file.
  • Set the value of TRAININGSET_PATH in params.py, which means where the training files saved.
  • run ae_estimator.py for training

In our case

  • There are 145 transient images in training set and 37 transient images in test set.
  • We sample 6000 patchs(1 x 4096 x 9 x 9 x 1) from each transient images, so there are 870000 samples
  • We randomly save them in 40 ".h5" files, each files have 21750 samples and the shape of the dataset('/training_set') is "21750 x 4096 x 9 x 9 x 1". So we set the N_FILE_SAMPE 21750
  • These files are saved in "F:/9x9_6000sample/", so we set TRAININGSET_PATH "F:/9x9_6000sample/"

Citation

@inproceedings{liang2019data,
  title={A data-driven compression method for transient rendering},
  author={Liang, Yun and Chen, Mingqin and Huang, Zesheng and Gutierrez, Diego and Mu{\~n}oz, Adolfo and Marco, Julio},
  booktitle={ACM SIGGRAPH 2019 Posters},
  pages={33},
  year={2019},
  organization={ACM}
}
@article{liang2020compression,
  title={Compression and Denoising of Transient Light Transport},
  author={Liang, Yun and Chen, Mingqin and Huang, Zesheng and Gutierrez, Diego and Mu{\~n}oz, Adolfo and Marco, Julio},
  journal={Optics Letters},
  year={2020},
}

Contacts

For questions, please send an email to [email protected]