Geometric Partitioning Mode in Versatile Video Coding: Algorithm Review and Analysis

Gao, Han; Esenlik, Semih; Alshina, Elena; Steinbach, Eckehard

doi:10.1109/tcsvt.2020.3040291

Cited by 26 publications

(10 citation statements)

References 24 publications

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“…The GPM [22]- [24] aims to increase the partition precision and to better fit the moving objects boundaries using a geometrical partition of a coding tree leaf node CU. Because of the more flexible partitioning and the blending process, the GPM is benefit to video contents that include rigid moving objects relative to static background or other moving objects.…”

Section: Geometric Partitioning Modementioning

confidence: 99%

“…Therefore, the presented algorithm has been adopted in VVC. This section briefly presented the algorithm of GPM, for further background logic, comprehensive description, and statistical analysis, readers can refer to [24].…”

Section: Geometric Partitioning Modementioning

confidence: 99%

“…• Motion vector (MV) coding: MV predictor (MVP) candidate list with 2 candidates generated based on spatial/temporal MV predictors or MVs from historybased motion vector prediction(HMVP) tables [8], [9]; symmetric MV difference(SMVD) that signals a pair of symmetric bi-prediction MV differences (MVDs) with slice-level indicated reference pictures [10], [11]; adaptive MV resolution (AMVR) for MV predictors and MVDs at 1) quarter-to 4-luma samples or 2) one-16th-to one-luma sample precision depending on selected motion models, i.e., 1) for the translational motion model and 2) for the affine motion model [13]- [18]; • Block merging: block merging candidate list with at most 6 candidates generated based on spatial/temporal, candidates from HMVP tables and a synthetic pairwise motion vector predictor; geometric partitioning mode (GPM) that geometrically splits a block at an angle of power-of-two tangent with a boundaryshifting offset [22]- [24]; merge mode with MV difference(MMVD) that allows adding power-of-2 1-D offsets to either horizontal or vertical components of a selected merge candidate [22], [23]; combined inter-intra prediction (CIIP) to generate a prediction block with weighted combination of a planar intra predictor and the motioncompensated temporal predictor of a selected merge candidate [25], [26]; merge estimation region (MER) to allow independent/parallel derivation of MV prediction list and merge candidate list of coding units (CUs) inside the region [27]; • Others: bidirectional prediction with coding unit weights (BCW) to introduce non-equal weights at CU level for bi-prediction [28]- [30]; motion vector compression and range to encode motion fields on reference pictures by using a 10-bit mantissa-exponent representation at every 8 × 8 grid [31].…”

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confidence: 99%

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Motion Vector Coding and Block Merging in the Versatile Video Coding Standard

Chien

Zhang²,

Winken

et al. 2021

IEEE Trans. Circuits Syst. Video Technol.

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This paper overviews the motion vector coding and block merging techniques in the Versatile Video Coding (VVC) standard developed by the Joint Video Experts Team (JVET). In general, inter-prediction techniques in VVC can be classified into two major groups: "whole block-based inter prediction" and "subblock-based inter prediction". In this paper, we focus on techniques for whole block-based inter prediction. As in its predecessor, High Efficiency Video Coding (HEVC), whole block-based inter prediction in VVC is represented by adaptive motion vector prediction (AMVP) mode or merge mode. Newly introduced features purely for AMVP mode include symmetric motion vector difference and adaptive motion vector resolution. The features purely for merge mode include pairwise average merge, merge with motion vector difference, combined interintra prediction and geometric partitioning mode. Coding tools such as history-based motion vector prediction and bidirectional prediction with coding unit weights can be applied on both AMVP mode and merge mode. This paper discusses the design principles and the implementation of the new inter-prediction methods. Using objective metrics, simulation results show that the methods overviewed in the paper can jointly achieve 6.2% and 4.7% BD-rate savings on average with the random access and low-delay configurations, respectively. Significant subjective picture quality improvements of some tools are also reported when comparing the resulting pictures at same bitrates.

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Section: Geometric Partitioning Modementioning

confidence: 99%

Section: Geometric Partitioning Modementioning

confidence: 99%

mentioning

confidence: 99%

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Motion Vector Coding and Block Merging in the Versatile Video Coding Standard

Chien

Zhang²,

Winken

et al. 2021

IEEE Trans. Circuits Syst. Video Technol.

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“…VVC enhances many of the inter prediction tools from HEVC, including the conventional ME and merge mode. The main VVC novelties are: (i) the use of Affine Motion Compensation (AMC) [24], to represent higher-order motion beyond translation, such as rotation, scaling, and shearing; (ii) the increase in the motion vector (MV) precision to 1/16 (compared to 1/4 in HEVC); (iii) Adaptive Motion Vector Resolution (AMVR), that allows the selection of the MV precision according to the coded mode [25]; (iv) Geometric Partitioning Mode (GPM) [26], which splits a CU into two non-rectangular partitions to perform the inter prediction separately; (v) Combined Inter and Intra Prediction (CIIP), which combines the inter prediction (merge mode) with the intra prediction (planar mode) [27]; (vi) Decoder-side MV refinement (DMVR), intending to improve the compression efficiency [28]; (vii) Bidirectional Optical Flow (BDOF), which explores the optical flow concept [29]; (viii) Prediction Refinement with Optical Flow (PROF), used for affine prediction also exploring the optical flow concept [4]; (ix) Bi-prediction with CU-level Weights (BCW), which uses till five predefined weights instead of the traditional weighted prediction [4]; (x) Extended Merge Prediction, allowing a new set of tools to improve the merge process [4].…”

Section: Inter Predictionmentioning

confidence: 99%

AV1 and VVC Video Codecs: Overview on Complexity Reduction and Hardware Design

Corrêa

Saldanha

Borges

et al. 2021

IEEE Open J. Circuits Syst.

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This article presents an extensive review of the state-of-the-art system-level solutions featuring complexity reduction and/or dedicated hardware designs for the AV1 and VVC video coding formats. These formats introduced several novel coding techniques compared to their predecessors to improve the coding efficiency at the cost of a significant computational cost. In this article, we discuss the main novelties of AV1 and VVC in each coding module, including block partitioning, intra and inter prediction, transform, entropy coding, and in-loop filters. Then, we present the main published works focusing on complexity reduction and hardware designs for AV1 and VVC. Most of the complexity reduction solutions target the complex and flexible block partitioning structures of these encoders to provide a better tradeoff between coding efficiency and complexity reduction whereas the hardware designs focus on the challenge of implementing the new coding tools to attend real-time processing of high-definition videos. Even with the presented works reaching impressive results, these research fields remain opened for innovative contributions, as discussed in this article.

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“…The overview of the GPM in VVC is shown in Fig. 1 (a) [4], [5]. Different from the regular inter prediction performed on rectangular blocks in VVC, the GPM separates a coding block into two regions by the predefined 64 types of straight lines, generates inter predicted sampling values of luma and chroma component signals ("samples" hereinafter) for each GPM-separated region (P 0 , P 1 ) with different motion vectors (MV 0 , MV 1 ), and then blends them to obtain the final inter predicted samples (P G ).…”

Section: Introductionmentioning

confidence: 99%

Geometric Partitioning Mode with Inter and Intra Prediction for Beyond Versatile Video Coding

Kidani

Kato

Kawamura

et al. 2022

IEICE Trans. Inf. & Syst.

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Geometric partitioning mode (GPM) is a new inter prediction tool adopted in versatile video coding (VVC), which is the latest video coding of international standard developed by joint video expert team in 2020. Different from the regular inter prediction performed on rectangular blocks, GPM separates a coding block into two regions by the predefined 64 types of straight lines, generates inter predicted samples for each separated region, and then blends them to obtain the final inter predicted samples. With this feature, GPM improves the prediction accuracy at the boundary between the foreground and background with different motions. However, GPM has room to further improve the prediction accuracy if the final predicted samples can be generated using not only inter prediction but also intra prediction. In this paper, we propose a GPM with inter and intra prediction to achieve further enhanced compression capability beyond VVC. To maximize the coding performance of the proposed method, we also propose the restriction of the applicable intra prediction mode number and the prohibition of applying the intra prediction to both GPM-separated regions. The experimental results show that the proposed method improves the coding performance gain by the conventional GPM method of VVC by 1.3 times, and provides an additional coding performance gain of 1% bitrate savings in one of the coding structures for low-latency video transmission where the conventional GPM method cannot be utilized.

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Geometric Partitioning Mode in Versatile Video Coding: Algorithm Review and Analysis

Cited by 26 publications

References 24 publications

Motion Vector Coding and Block Merging in the Versatile Video Coding Standard

Motion Vector Coding and Block Merging in the Versatile Video Coding Standard

AV1 and VVC Video Codecs: Overview on Complexity Reduction and Hardware Design

Geometric Partitioning Mode with Inter and Intra Prediction for Beyond Versatile Video Coding

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