Neural Networks Based Fractional Pixel Motion Estimation for HEVC

Ibrahim, Ehab M.; Badry, Emad; Abdelsalam, Ahmed M.; Abdalla, Ibrahim L.; Sayed, Mohammed S.; Shalaby, Hossam M. H.

doi:10.1109/ism.2018.00027

Cited by 5 publications

(3 citation statements)

References 14 publications

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“…In [186], a cascade neural network of a fully connected network (FCN) and a CNN is proposed for inter prediction algorithm in HEVC, in which the spatial neighboring pixels and the temporal neighboring pixels are fed to the network to perform accurate inter prediction. A fully connected networks-based interpolation-free FME scheme is proposed in [187], which utilizes the SSE of best IME and eight surrounding locations, PB height and width to predicts the best FME. In [188], a group variational transformation convolutional neural network (GVTCNN) were designed to improve the fractional interpolation performance of the luma component in motion compensation, which infers samples at different sub-pixel positions from the input integer-position sample.…”

Section: Finer Precision Motion Estimation and Compensationmentioning

confidence: 99%

“…2 The two sets of BD-Rate are under different training/testing conditions, while the encoding/decoding time is identical. [186] HM 16.9 LDP -1.7 3444 Ibrahim2018 [187] HM 16.9 LDP -2.6 --Xia 2018 [188] HM16.15 LDP -1.9 --Zhao 2019 [189] HM16.15 RA/LDB -3.0/-1.6 164.9/-and dozens of work have been proposed for almost all modules along the coding/decoding process, including intra CU partitioning [190][191][192][193], block up-sampling for intra frame coding [194], intra mode decision [195][196][197][198][199], transform [200], rate control [201,202], in-loop filtering/post-processing [203][204][205], arithmetic coding [206], or decoder-end artifact-removal and quality enhancement [207,208].…”

Section: Deep Learning-based Inter Codingmentioning

confidence: 99%

Section: Deep Learning-based Inter Codingmentioning

confidence: 99%

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Recent Advances on HEVC Inter-Frame Coding: From Optimization to Implementation and Beyond

Zhang

Fan

et al. 2020

IEEE Trans. Circuits Syst. Video Technol.

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High Efficiency Video Coding (HEVC) has doubled the video compression ratio with equivalent subjective quality as compared to its predecessor H.264/AVC. The significant coding efficiency improvement is attributed to many new techniques. Interframe coding is one of the most powerful yet complicated techniques therein and has posed high computational burden thus main obstacle in HEVC-based real-time applications. Recently, plenty of research has been done to optimize the inter-frame coding, either to reduce the complexity for real-time applications, or to further enhance the encoding efficiency. In this paper, we provide a comprehensive review of the state-of-the-art techniques for HEVC inter-frame coding from three aspects, namely fast inter coding solutions, implementation on different hardware platforms as well as advanced inter coding techniques. More specifically, different algorithms in each aspect are further subdivided into sub-categories and compared in terms of pros, cons, coding efficiency and coding complexity. To the best of our knowledge, this is the first such comprehensive review of the recent advances of the inter-frame coding for HEVC and hopefully it would help the improvement, implementation and applications of HEVC as well as the ongoing development of the next generation video coding standard.

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Section: Finer Precision Motion Estimation and Compensationmentioning

confidence: 99%