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README

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:

Path Files Format Description
dataset Main folder
├─  data_scripts 4 .py Python scripts to process downloaded dataset.
├─  synthetic_data Synthetic dataset.
      └─  GT Reprojected and cropped HDR images at 800×800.
             ├─  train 2,016 .npy Training split.
             └─  test 360 .npy Test split.
├─  real_data Real dataset.
      ├─  input 30 .npy Input UDC images at 3264×2448, captured by ZTE phone.
      ├─  CCM_txt 30 .txt Color correction matrix for each real input image.
      └─  jpg_ZTE 30 .jpg Camera output after built-in ISP.
├─  PSF PSF-related files.
      ├─  kernel_code 9 .npy Kernel code generated by PCA, d=5.
      ├─  kernel_info_list .txt List to specify iamges with corresponding path of PSF. To be generated by a script.
      └─  ZTE_new 9 .npy PSFs 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}
}