… -end compression have thus been reimplemented in PyTorch and trained from scratch. We
also report objective comparison results using PSNR and MS-SSIM metrics vs. bit-rate, using …

… However, we find it peculiar to find that for some metrics (eg, SSIM, MS-SSIM, VSI) the
same implementation exactly matches with only one of two reference values. Note 2: All three …

… Our OpenDVC (MS-SSIM) model provides a more convincing baseline for MS-SSIM optimized
methods, which can only compare with the … A reimplementation of SPyNet using PyTorch. …

… We use Pytorch and NVIDIA 1080Ti GPU for training and test, except for the memory … To
simplify the training process, we use MS-SSIM for training the partial post-processing network …

… The SSIM ratings are calculated using Pytorch MS-SSIM1. For ViSQOL and FAD, the
clips are downmixed into mono and converted from 32-bit to 16-bit WAV files. Ratings are …

… 5 , otherwise Since MS-SSIM is an image quality-based measure that we aim to maximize,
the MS-SSIM cost term is … We have implemented the network in the PyTorch framework. The …

… Occasionally, MS-SSIM and similar metrics are used. The pre-trained classification … with
Pytorch, and the variants of their metrics were differentiable. Due to PSNR, SSIM, MS-SSIM and …

… In our challenge, PSNR and MS-SSIM are calculated in the RGB domain on each frame, and
… in the fidelity tracks depends on PSNR, and we additionally report MS-SSIM for analyses. …

… When using MS-SSIM for performance evaluation, we further fine-tune … MS-SSIM as the
distortion loss to achieve better MS-SSIM results. Our method is implemented based on PyTorch …

… Deep learning framework PyTorch [14] is used for implementing the proposed learned … We
report the average of PSNR/MS-SSIM of individual frames over the whole dataset in order to …