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Italiano(IT) tcnerv:dual-domain temporal context modeling for implicit neural video compression

TCNeRV advances neural video compression with dual-domain temporal context

By PulseAugur Editorial · [1 sources] ·

Researchers have developed TCNeRV, a novel approach to implicit neural video compression that improves reconstruction quality by leveraging temporal context from both feature and embedding domains. The system incorporates a multi-scale temporal-context fusion module and a temporal embedding-residual coding method to condition intermediate features and predict content embeddings. With approximately 3 million parameters, TCNeRV has demonstrated significant reductions in BD-rate compared to existing methods on the UVG dataset, achieving a competitive average PSNR of 36.08 dB. AI

IMPACT This research could lead to more efficient video compression techniques, impacting storage and streaming technologies.

RANK_REASON This is a research paper detailing a new method for implicit neural video compression. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

TCNeRV advances neural video compression with dual-domain temporal context

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This is a research paper detailing a new method for implicit neural video compression. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 Italiano(IT) · Xuezhi Xiang, Yixin Zhao, Heqi Xiang, Jiayao Liu, Shanjun Zhang ·

    tcnerv: dual-domain temporal context modeling for implicit neural video compression

    arXiv:2609.16870v1 Announce Type: new Abstract: Video compression aims to minimize reconstruction distor tion under a constrained bit rate. Existing video implicit neural representations (INRs) often decode frames independently, leaving intermediate features unconditioned on prev…

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