2022/05/19 by Duolikun Danier, Feng Chen, Danier, Duolikun +5
Computer Science · #Advanced Image Processing Techniques #Advanced Vision and Imaging #Digital Media Forensic Detection #FOS: Electrical engineering #Image and Video Processing (eess.IV) #electronic engineering #information engineering
paper · doi:10.48550/arxiv.2205.09458
openalex publication_date 2022/05/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper describes a CNN-based multi-frame post-processing approach based on a perceptually-inspired Generative Adversarial Network architecture, CVEGAN. This method has been integrated with the Versatile Video Coding Test Model (VTM) 15.2 to enhance the visual quality of the final reconstructed content. The evaluation results on the CLIC 2022 validation sequences show consistent coding gains over the original VVC VTM at the same bitrates when assessed by PSNR. The integrated codec has been submitted to the Challenge on Learned Image Compression (CLIC) 2022 (video track), and the team name associated with this submission is BVIVC.