README

April 19, 2021 · View on GitHub

This is a image dataset created as a benchmark for Under-Display Camera (UDC) image restoration, released by CVPR'21 paper:

Removing Diffraction Image Artifacts in Under-Display Camera via Dynamic Skip Connection Network
Ruicheng Feng, Chongyi Li, Huaijin Chen, Shuai Li, Chen Change Loy, Jinwei Gu
Computer Vision and Pattern Recognition (CVPR), 2021

For more information, please visit the project page: https://jnjaby.github.io/projects/UDC/

Overview

All data is hosted on Google Drive:

PathFilesFormatDescription
datasetMain folder
├─  data_scripts4.pyPython scripts to process downloaded dataset.
├─  synthetic_dataSynthetic dataset.
      └─  GTReprojected and cropped HDR images at 800×800.
             ├─  train2,016.npyTraining split.
             └─  test360.npyTest split.
├─  real_dataReal dataset.
      ├─  input30.npyInput UDC images at 3264×2448, captured by ZTE phone.
      ├─  CCM_txt30.txtColor correction matrix for each real input image.
      └─  jpg_ZTE30.jpgCamera output after built-in ISP.
├─  PSFPSF-related files.
      ├─  kernel_code9.npyKernel code generated by PCA, d=5.
      ├─  kernel_info_list.txtList to specify iamges with corresponding path of PSF. To be generated by a script.
      └─  ZTE_new9.npyPSFs in various angles, size 800×800.

Dataset

Collected data are processed in the following order:

  1. Download and unzip datasets into current directory:

    python data_scripts/download_dataset.py --dataset=UDC
    

    Alternatively, you can also download the data directly from GoogleDrive, unzip and put them into ./datasets.

  2. Generating synthetic data by apply convolution with PSF for UDC simulation:

    python data_scripts/data_simulation.py --data_path=. --psf_type=ZTE_new
    
  3. Generating info list of images together with corresponding PSF:

    python data_scripts/generate_info_list.py --data_path=. --psf_type=ZTE_new --save_dir=./PSF/kernel_info_list
    

Citation

If you use the dataset in your publication, please consider citing our paper:

@inproceedings{feng2021removing,
    author = {Feng, Ruicheng and Li, Chongyi and Chen, Huaijin and Li, Shuai and Loy, Chen Change and Gu, Jinwei},
    title = {Removing Diffraction Image Artifacts in Under-Display Camera via Dynamic Skip Connection Networks},
    booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
    year = {2021}
}