This is the implementation of BNUDC: A Two-Branched Deep Neural Network for Restoring Images from Under-Display Cameras (CVPR, 2022).
Now constructing....
You can train or test the BNUDC by changing options; exp_name
; and data_root
in options/base_options.py
, and run train.py
or test.py
.
The datasets are available at POLED containing the pre-processed UDC images, TOLED and SYNTH
Three pre-trained weights for these datasets can be downloaded at CHECKPOINTS.
@InProceedings{Koh_2022_CVPR,
author = {Koh, Jaihyun and Lee, Jangho and Yoon, Sungroh},
title = {BNUDC: A Two-Branched Deep Neural Network for Restoring Images From Under-Display Cameras},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2022},
pages = {1950-1959}
}