Conditional Neural Video Coding with Spatial-Temporal Super-Resolution

Fuente: arXiv
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Autori principali: Wang, Henan, Pan, Xiaohan, Feng, Runsen, Guo, Zongyu, Chen, Zhibo
Natura: Preprint
Pubblicazione: 2024
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author Wang, Henan
Pan, Xiaohan
Feng, Runsen
Guo, Zongyu
Chen, Zhibo
author_facet Wang, Henan
Pan, Xiaohan
Feng, Runsen
Guo, Zongyu
Chen, Zhibo
contents This document is an expanded version of a one-page abstract originally presented at the 2024 Data Compression Conference. It describes our proposed method for the video track of the Challenge on Learned Image Compression (CLIC) 2024. Our scheme follows the typical hybrid coding framework with some novel techniques. Firstly, we adopt Spynet network to produce accurate motion vectors for motion estimation. Secondly, we introduce the context mining scheme with conditional frame coding to fully exploit the spatial-temporal information. As for the low target bitrates given by CLIC, we integrate spatial-temporal super-resolution modules to improve rate-distortion performance. Our team name is IMCLVC.
format Preprint
id arxiv_https___arxiv_org_abs_2401_13959
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Conditional Neural Video Coding with Spatial-Temporal Super-Resolution
Wang, Henan
Pan, Xiaohan
Feng, Runsen
Guo, Zongyu
Chen, Zhibo
Image and Video Processing
Computer Vision and Pattern Recognition
This document is an expanded version of a one-page abstract originally presented at the 2024 Data Compression Conference. It describes our proposed method for the video track of the Challenge on Learned Image Compression (CLIC) 2024. Our scheme follows the typical hybrid coding framework with some novel techniques. Firstly, we adopt Spynet network to produce accurate motion vectors for motion estimation. Secondly, we introduce the context mining scheme with conditional frame coding to fully exploit the spatial-temporal information. As for the low target bitrates given by CLIC, we integrate spatial-temporal super-resolution modules to improve rate-distortion performance. Our team name is IMCLVC.
title Conditional Neural Video Coding with Spatial-Temporal Super-Resolution
topic Image and Video Processing
Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2401.13959