22 citations · 37 across the 5 of their papers we have counts for
5 papers
Content Adaptive Encoding For Interactive Game Streaming
Shakarim Soltanayev, Odysseas Zisimopoulos, Mohammad Ashraful Anam +3
Video-on-demand streaming has benefitted from \textit{content-adaptive encoding} (CAE), i.e., adaptation of resolution and/or quantization parameters for each scene based on convex…
NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video: Dataset, Methods and Results
Ren Yang, Radu Timofte, Meisong Zheng +75
This paper reviews the NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video. In this challenge, we proposed the LDV 2.0 dataset, which includes the…
Extending Stein's unbiased risk estimator to train deep denoisers with correlated pairs of noisy images
Magauiya Zhussip, Shakarim Soltanayev, Se Young Chun
Recently, Stein's unbiased risk estimator (SURE) has been applied to unsupervised training of deep neural network Gaussian denoisers that outperformed classical non-deep learning b…
Training deep learning based image denoisers from undersampled measurements without ground truth and without image prior
Magauiya Zhussip, Shakarim Soltanayev, Se Young Chun
Compressive sensing is a method to recover the original image from undersampled measurements. In order to overcome the ill-posedness of this inverse problem, image priors are used…
Training Deep Learning Based Denoisers without Ground Truth Data
Shakarim Soltanayev, Se Young Chun
Recently developed deep-learning-based denoisers often outperform state-of-the-art conventional denoisers such as the BM3D. They are typically trained to minimize the mean squared…