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Calculation of average PSNR differences between RD-curves

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The article was published on 2001-01-01 and is currently open access. It has received 4379 citations till now.

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Machine Learning-Based Coding Unit Depth Decisions for Flexible Complexity Allocation in High Efficiency Video Coding

TL;DR: A machine learning-based fast coding unit (CU) depth decision method for High Efficiency Video Coding (HEVC), which optimizes the complexity allocation at CU level with given rate-distortion (RD) cost constraints.
Journal ArticleDOI

Content-Aware Convolutional Neural Network for In-Loop Filtering in High Efficiency Video Coding

TL;DR: This paper quantitatively analyzes the structure of the proposed CNN model from multiple dimensions to make the model interpretable and optimal for CNN-based loop filtering for high-efficiency video coding (HEVC).
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Variable block size transforms for hybrid video coding

Mathias Wien
TL;DR: In this paper, the authors propose a method to solve the problem of "uniformity" and "unweighting" of the problem: "uncertainty" is introduced.
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Improved Lossy Image Compression with Priming and Spatially Adaptive Bit Rates for Recurrent Networks

TL;DR: A method for lossy image compression based on recurrent, convolutional neural networks that outperforms BPG, WebP, JPEG2000, and JPEG as measured by MS-SSIM is proposed and it is shown that training with a pixel-wise loss weighted by SSIM increases reconstruction quality according to multiple metrics.
Journal ArticleDOI

Low-Complexity CTU Partition Structure Decision and Fast Intra Mode Decision for Versatile Video Coding

TL;DR: A fast intra-coding algorithm consisting of low-complexity coding tree units (CTU) structure decision and fast intra mode decision and the complexity reduction of the proposed algorithm is up to 70% compared to VVC reference software, and averagely 63% encoding time saving is achieved.
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