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Main Authors: Yang, Jiayu, Jiang, Wei, Zhai, Yongqi, Yang, Chunhui, Wang, Ronggang
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2402.01289
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author Yang, Jiayu
Jiang, Wei
Zhai, Yongqi
Yang, Chunhui
Wang, Ronggang
author_facet Yang, Jiayu
Jiang, Wei
Zhai, Yongqi
Yang, Chunhui
Wang, Ronggang
contents This paper presents a learned video compression method in response to video compression track of the 6th Challenge on Learned Image Compression (CLIC), at DCC 2024.Specifically, we propose a unified contextual video compression framework (UCVC) for joint P-frame and B-frame coding. Each non-intra frame refers to two neighboring decoded frames, which can be either both from the past for P-frame compression, or one from the past and one from the future for B-frame compression. In training stage, the model parameters are jointly optimized with both P-frames and B-frames. Benefiting from the designs, the framework can support both P-frame and B-frame coding and achieve comparable compression efficiency with that specifically designed for P-frame or B-frame.As for challenge submission, we report the optimal compression efficiency by selecting appropriate frame types for each test sequence. Our team name is PKUSZ-LVC.
format Preprint
id arxiv_https___arxiv_org_abs_2402_01289
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle UCVC: A Unified Contextual Video Compression Framework with Joint P-frame and B-frame Coding
Yang, Jiayu
Jiang, Wei
Zhai, Yongqi
Yang, Chunhui
Wang, Ronggang
Computer Vision and Pattern Recognition
This paper presents a learned video compression method in response to video compression track of the 6th Challenge on Learned Image Compression (CLIC), at DCC 2024.Specifically, we propose a unified contextual video compression framework (UCVC) for joint P-frame and B-frame coding. Each non-intra frame refers to two neighboring decoded frames, which can be either both from the past for P-frame compression, or one from the past and one from the future for B-frame compression. In training stage, the model parameters are jointly optimized with both P-frames and B-frames. Benefiting from the designs, the framework can support both P-frame and B-frame coding and achieve comparable compression efficiency with that specifically designed for P-frame or B-frame.As for challenge submission, we report the optimal compression efficiency by selecting appropriate frame types for each test sequence. Our team name is PKUSZ-LVC.
title UCVC: A Unified Contextual Video Compression Framework with Joint P-frame and B-frame Coding
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2402.01289