Test Code for CVQENet: CVQENet: Deformable Convolution-based Compressed Video Quality Enhancement Network, which took the 8th place in Track1 of the NTIRE 2021 Challenge on Quality Enhancement of Compressed Video. More challenge details can be seen in https://github.com/RenYang-home/NTIRE21_VEnh Environment: pytorch:1.2 Prerequest: 1. cd code/ops/dcn/ 2. bash build.sh 3. python simple_check.py Test: 1. cd code 2. option setting - pretrain: the path of the pretrained model, e.g. ../pretrainModel - nb1 : the number of reblock in FEM, our pretrained model is nb1 = 10 - nb2 : the number of reblock in FQEM, our pretrained model is nb2 = 20 - nf : the number of channel, our pretrained model is nf = 64 - test_dir: the path of testing video images - image_out: the path to save the output image 3. run code, python test.py Acknowledgement: Our code is based on : https://github.com/RyanXingQL/STDF-PyTorch and https://github.com/xinntao/EDVR Concat: If you have any question, drop us a line at chenyiyun1994@outlook.com or simply open a new issue.