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Conditional Neural Video Coding with Spatial-Temporal Super-Resolution

arXiv 2401.13959 ↗First posted 25 Jan 2024eess.IV cs.CVcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 13 of its 15 references that are in the map. First posted on arXiv 25 Jan 2024.

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13 of 15 references.

References · 13

  1. 2016Optical Flow Estimation using a Spatial Pyramid Networkcited by 424
  2. 2018DVC: An End-to-end Deep Video Compression Frameworkcited by 332
  3. 2022ELIC: Efficient Learned Image Compression with Unevenly Grouped Space-Channel Contextual Adaptive Codingcited by 301
  4. 2021Deep Contextual Video Compressioncited by 221
  5. 2023Neural Video Compression with Diverse Contextscited by 165
  6. 2021FVC: A New Framework towards Deep Video Compression in Feature Spacecited by 153
  7. 2021Temporal Context Mining for Learned Video Compressioncited by 117
  8. 2023Extracting Motion and Appearance via Inter-Frame Attention for Efficient Video Frame Interpolationcited by 98
  9. 2021ELF-VC: Efficient Learned Flexible-Rate Video Codingcited by 69
  10. 2022Coarse-to-fine Deep Video Coding with Hyperprior-guided Mode Predictioncited by 55
  11. 2022CANF-VC: Conditional Augmented Normalizing Flows for Video Compressioncited by 46
  12. 2021End-to-End Rate-Distortion Optimized Learned Hierarchical Bi-Directional Video Compressioncited by 28
1 more
  1. 2021Learning Cross-Scale Weighted Prediction for Efficient Neural Video Compressioncited by 13

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