Relevant bibliographies by topics / Versatile Video Coding

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Versatile Video Coding'

Author: Grafiati
Published: 25 May 2024
Last updated: 1 June 2024

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Journal articles on the topic "Versatile Video Coding"

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Choe, Jaeryun, Haechul Choi, Heeji Han, and Daehyeok Gwon. "Novel video coding methods for versatile video coding." International Journal of Computational Vision and Robotics 11, no. 5 (2021): 526. http://dx.doi.org/10.1504/ijcvr.2021.10040489.

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Han, Heeji, Daehyeok Gwon, Jaeryun Choe, and Haechul Choi. "Novel video coding methods for versatile video coding." International Journal of Computational Vision and Robotics 11, no. 5 (2021): 526. http://dx.doi.org/10.1504/ijcvr.2021.117582.

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Takamura, Seishi. "Versatile Video Coding: a Next-generation Video Coding Standard." NTT Technical Review 17, no. 6 (June 2019): 49–52. http://dx.doi.org/10.53829/ntr201906gls.

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Silva, Giovane Gomes, Ícaro Gonçalves Siqueira, Mateus Grellert, and Claudio Machado Diniz. "Approximate Hardware Architecture for Interpolation Filter of Versatile Video Coding." Journal of Integrated Circuits and Systems 16, no. 2 (August 15, 2021): 1–8. http://dx.doi.org/10.29292/jics.v16i2.327.

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The new Versatile Video Coding (VVC) standard was recently developed to improve compression efficiency of previous video coding standards and to support new applications. This was achieved at the cost of an increase in the computational complexity of the encoder algorithms, which leads to the need to develop hardware accelerators and to apply approximate computing techniques to achieve the performance and power dissipation required for systems that encode video. This work proposes the implementation of an approximate hardware architecture for interpolation filters defined in the VVC standard targeting real-time processing of high resolution videos. The architecture is able to process up to 2560x1600 pixels videos at 30 fps with power dissipation of 23.9 mW when operating at a frequency of 522 MHz, with an average compression efficiency degradation of only 0.41% compared to default VVC video encoder software configuration.
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Sullivan, Gary J. "Video Coding Standards Progress Report: Joint Video Experts Team Launches the Versatile Video Coding Project." SMPTE Motion Imaging Journal 127, no. 8 (September 2018): 94–98. http://dx.doi.org/10.5594/jmi.2018.2846098.

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Mishra, Amit Kumar. "Versatile Video Coding (VVC) Standard: Overview and Applications." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 10, no. 2 (September 10, 2019): 975–81. http://dx.doi.org/10.17762/turcomat.v10i2.13578.

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Information security includes picture and video compression and encryption since compressed data is more secure than uncompressed imagery. Another point is that handling data of smaller sizes is simple. Therefore, efficient, secure, and simple data transport methods are created through effective data compression technology. Consequently, there are two different sorts of compression algorithm techniques: lossy compressions and lossless compressions. Any type of data format, including text, audio, video, and picture files, may leverage these technologies. In this procedure, the Least Significant Bit technique is used to encrypt each frame of the video file format to be able to increase security. The primary goals of this procedure are to safeguard the data by encrypting the frames and compressing the video file. Using PSNR to enhance process throughput would also enhance data transmission security while reducing data loss.
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Palau, Roberta De Carvalho Nobre, Bianca Santos da Cunha Silveira, Robson André Domanski, Marta Breunig Loose, Arthur Alves Cerveira, Felipe Martin Sampaio, Daniel Palomino, Marcelo Schiavon Porto, Guilherme Ribeiro Corrêa, and Luciano Volcan Agostini. "Modern Video Coding: Methods, Challenges and Systems." Journal of Integrated Circuits and Systems 16, no. 2 (August 16, 2021): 1–12. http://dx.doi.org/10.29292/jics.v16i2.503.

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With the increasing demand for digital video applications in our daily lives, video coding and decoding become critical tasks that must be supported by several types of devices and systems. This paper presents a discussion of the main challenges to design dedicated hardware architectures based on modern hybrid video coding formats, such as the High Efficiency Video Coding (HEVC), the AOMedia Video 1 (AV1) and the Versatile Video Coding (VVC). The paper discusses eachstep of the hybrid video coding process, highlighting the main challenges for each codec and discussing the main hardware solutions published in the literature. The discussions presented in the paper show that there are still many challenges to be overcome and open research opportunities, especially for the AV1 and VVC codecs. Most of these challenges are related to the high throughput required for processing high and ultrahigh resolution videos in real time and to energy constraints of multimedia-capable devices.
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Adhuran, Jayasingam, Gosala Kulupana, Chathura Galkandage, and Anil Fernando. "Multiple Quantization Parameter Optimization in Versatile Video Coding for 360° Videos." IEEE Transactions on Consumer Electronics 66, no. 3 (August 2020): 213–22. http://dx.doi.org/10.1109/tce.2020.3001231.

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Li, Wei, Xiantao Jiang, Jiayuan Jin, Tian Song, and Fei Richard Yu. "Saliency-Enabled Coding Unit Partitioning and Quantization Control for Versatile Video Coding." Information 13, no. 8 (August 19, 2022): 394. http://dx.doi.org/10.3390/info13080394.

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The latest video coding standard, versatile video coding (VVC), has greatly improved coding efficiency over its predecessor standard high efficiency video coding (HEVC), but at the expense of sharply increased complexity. In the context of perceptual video coding (PVC), the visual saliency model that utilizes the characteristics of the human visual system to improve coding efficiency has become a reliable method due to advances in computer performance and visual algorithms. In this paper, a novel VVC optimization scheme compliant PVC framework is proposed, which consists of fast coding unit (CU) partition algorithm and quantization control algorithm. Firstly, based on the visual saliency model, we proposed a fast CU division scheme, including the redetermination of the CU division depth by calculating Scharr operator and variance, as well as the executive decision for intra sub-partitions (ISP), to reduce the coding complexity. Secondly, a quantization control algorithm is proposed by adjusting the quantization parameter based on multi-level classification of saliency values at the CU level to reduce the bitrate. In comparison with the reference model, experimental results indicate that the proposed method can reduce about 47.19% computational complexity and achieve a bitrate saving of 3.68% on average. Meanwhile, the proposed algorithm has reasonable peak signal-to-noise ratio losses and nearly the same subjective perceptual quality.
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PARK, Dohyeon, Jinho LEE, Jung-Won KANG, and Jae-Gon KIM. "Simplified Triangular Partitioning Mode in Versatile Video Coding." IEICE Transactions on Information and Systems E103.D, no. 2 (February 1, 2020): 472–75. http://dx.doi.org/10.1587/transinf.2019edl8084.

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Dissertations / Theses on the topic "Versatile Video Coding"

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Nasrallah, Anthony. "Novel compression techniques for next-generation video coding." Electronic Thesis or Diss., Institut polytechnique de Paris, 2021. http://www.theses.fr/2021IPPAT043.

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Le contenu vidéo occupe aujourd'hui environ 82% du trafic Internet mondial. Ce pourcentage important est dû à la révolution des contenus vidéo. D’autre part, le marché exige de plus en plus des vidéos avec des résolutions et des qualités plus élevées. De ce fait, développer des algorithmes de codage encore plus efficaces que ceux existants devient une nécessité afin de limiter afin de limiter l’augmentation de la quantité de données vidéo circulant sur internet et assurer une meilleure qualité de service. En outre, la consommation impressionnante de contenu multimédia dans les produits électroniques impacte l’aspect écologique. Par conséquent, trouver un compromis entre la complexité des algorithmes et l’efficacité des implémentations s’impose comme nouveau défi. Pour cela, une équipe collaborative a été créée dans le but de développer une nouvelle norme de codage vidéo, Versatile Video Coding – VVC/H.266. Bien que VVC ait pu aboutir à une réduction de plus de 40% du débit par rapport à HEVC, cela ne signifie pas du tout qu’il n’y a plus de besoin pour améliorer encore l’efficacité du codage. De plus, VVC ajoute une complexité remarquable par rapport à HEVC. Cette thèse vient répondre à ces problématiques en proposant trois nouvelles méthodes d'encodage. Les apports de cette recherche se répartissent en deux axes principaux. Le premier axe consiste à proposer et mettre en œuvre de nouveaux outils de compression dans la nouvelle norme, capables de générer des gains de codage supplémentaires. Deux méthodes ont été proposées pour ce premier axe. Le point commun entre ces deux méthodes est la dérivation des informations de prédiction du côté du décodeur. En effet, l’augmentation des choix de l’encodeur peut améliorer la précision des prédictions et donne moins de résidus d’énergie, conduisant à une réduction du débit. Néanmoins, plus de modes de prédiction impliquent plus de signalisation à envoyer dans le flux binaire pour informer le décodeur des choix qui ont été faits au niveau de l’encodeur. Les gains mentionnés ci-dessus sont donc largement compensés par la signalisation ajoutée. Si l’information de prédiction est dérivée au niveau du décodeur, ce dernier n’est plus passif, mais devient actif, c’est le concept de décodeur intelligent. Ainsi, il sera inutile de signaler l’information, d’où un gain en signalisation. Chacune des deux méthodes propose une technique intelligente différente pour prédire l’information au niveau du décodeur. La première technique construit un histogramme de gradients pour déduire différents modes de prédiction intra pouvant ensuite être combinés, pour obtenir le mode de prédiction intra final pour un bloc donné. Cette propriété de fusion permet de prédire plus précisément les zones avec des textures complexes, ce qui, dans les schémas de codage conventionnels, nécessiterait plutôt un partitionnement et/ou une transmission plus fine des résidus à haute énergie. La deuxième technique consiste à donner à VVC la possibilité de basculer entre différents filtres d’interpolation pour la prédiction inter. La déduction du filtre optimal sélectionné par l’encodeur est réalisée grâce à des réseaux de neurones convolutifs. Le deuxième axe, contrairement au premier, ne cherche pas à ajouter une contribution à l’algorithme de base de VVC. Cet axe vise plutôt à permettre une utilisation optimisée de l’algorithme déjà existant. L’objectif ultime est de trouver le meilleur compromis possible entre l’efficacité de compression fournie et la complexité imposée par les outils VVC. Ainsi, un système d’optimisation est conçu pour déterminer une technique efficace d’adaptation de l’activation des outils au contenu. La détermination de ces outils peut être effectuée soit en utilisant des réseaux de neurones artificiels, soit sans aucune technique d’intelligence artificielle
Video content now occupies about 82% of global internet traffic. This large percentage is due to the revolution in video content consumption. On the other hand, the market is increasingly demanding videos with higher resolutions and qualities. This causes a significant increase in the amount of data to be transmitted. Hence the need to develop video coding algorithms even more efficient than existing ones to limit the increase in the rate of data transmission and ensure a better quality of service. In addition, the impressive consumption of multimedia content in electronic products has an ecological impact. Therefore, finding a compromise between the complexity of algorithms and the efficiency of implementations is a new challenge. As a result, a collaborative team was created with the aim of developing a new video coding standard, Versatile Video Coding – VVC/H.266. Although VVC was able to achieve a more than 40% reduction in throughput compared to HEVC, this does not mean at all that there is no longer a need to further improve coding efficiency. In addition, VVC adds remarkable complexity compared to HEVC. This thesis responds to these problems by proposing three new encoding methods. The contributions of this research are divided into two main axes. The first axis is to propose and implement new compression tools in the new standard, capable of generating additional coding gains. Two methods have been proposed for this first axis. These two methods rely on the derivation of prediction information at the decoder side. This is because increasing encoder choices can improve the accuracy of predictions and yield less energy residue, leading to a reduction in bit rate. Nevertheless, more prediction modes involve more signaling to be sent into the binary stream to inform the decoder of the choices that have been made at the encoder. The gains mentioned above are therefore more than offset by the added signaling. If the prediction information has been derived from the decoder, the latter is no longer passive, but becomes active hence the concept of intelligent decoder. Thus, it will be useless to signal the information, hence a gain in signalization. Each of the two methods offers a different intelligent technique than the other to predict information at the decoder level. The first technique constructs a histogram of gradients to deduce different intra-prediction modes that can then be combined by means of prediction fusion, to obtain the final intra-prediction for a given block. This fusion property makes it possible to more accurately predict areas with complex textures, which, in conventional coding schemes, would rather require partitioning and/or finer transmission of high-energy residues. The second technique gives VVC the ability to switch between different interpolation filters of the inter prediction. The deduction of the optimal filter selected by the encoder is achieved through convolutional neural networks. The second axis, unlike the first, does not seek to add a contribution to the VVC algorithm. This axis rather aims to build an optimized use of the already existing algorithm. The ultimate goal is to find the best possible compromise between the compression efficiency delivered and the complexity imposed by VVC tools. Thus, an optimization system is designed to determine an effective technique for activating the new coding tools. The determination of these tools can be done either using artificial neural networks or without any artificial intelligence technique
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Aklouf, Mourad. "Video for events : Compression and transport of the next generation video codec." Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPASG029.

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L'acquisition et la diffusion de contenus avec une latence minimale sont devenus essentiel dans plusieurs domaines d'activités tels que la diffusion d'évènements sportifs, la vidéoconférence, la télé-présence, la télé-opération de véhicules ou le contrôle à distance de systèmes. L'industrie de la diffusion en direct a connu une croissance en 2020, et son importance va encore croitre au cours des prochaines années grâce à l'émergence de nouveaux codecs vidéo à haute efficacité reposant sur le standard Versatile Video Coding(VVC)et à la cinquième génération de réseaux mobiles (5G).Les méthodes de streaming de type HTTP Adaptive Streaming (HAS) telles que MPEG-DASH, grâce aux algorithmes d'adaptation du débit de transmission de vidéo compressée, se sont révélées très efficaces pour améliorer la qualité d'expérience (QoE) dans un contexte de vidéo à la demande (VOD).Cependant, dans les applications où la latence est critique, minimiser le délai entre l'acquisition de l'image et son affichage au récepteur est essentiel. La plupart des algorithmes d'adaptation de débit sont développés pour optimiser la transmission vidéo d'un serveur situé dans le cœur de réseau vers des clients mobiles. Dans les applications nécessitant un streaming à faible latence, le rôle du serveur est joué par un terminal mobile qui va acquérir, compresser et transmettre les images via une liaison montante comportant un canal radio vers un ou plusieurs clients. Les approches d'adaptation de débit pilotées par le client sont par conséquent inadaptées. De plus, les HAS, pour lesquelles la prise de décision se fait avec une périodicité de l'ordre de la seconde ne sont pas suffisamment réactives lors d'une mobilité importante du serveur et peuvent engendrer des délais importants. Il est donc essentiel d'utiliser une granularité d'adaptation très fine afin de réduire le délai de bout-en-bout. En effet, la taille réduite des tampons d'émission et de réception afin de minimiser la latence rend plus délicate l'adaptation du débit dans notre cas d'usage. Lorsque la bande passante varie avec une constante de temps plus petite que la période avec laquelle la régulation est faite, les mauvaises décisions de débit de transmission peuvent induire un surcroit de latence important.L'objet de cette thèse est d'apporter des éléments de réponse à la problématique de la transmission vidéo à faible latence depuis des terminaux (émetteurs) mobiles. Nous présentons d'abord un algorithme d'adaptation de débit image-par-image pour la diffusion à faible latence. Une approche de type Model Predictive Control (MPC) est proposée pour déterminer le débit de codage de chaque image à transmettre. Cette approche utilise des informations relatives au niveau de tampon de l'émetteur et aux caractéristiques du canal de transmission. Les images étant codées en direct, un modèle reliant le paramètre de quantification (QP) au débit de sortie du codeur vidéo est nécessaire. Nous avons donc proposé un nouveau modèle reliant le débit au paramètre de quantification et à la distorsion de l'image précédente. Ce modèle fournit de bien meilleurs résultats dans le contexte d'une décision prise image par image du débit de codage que les modèle de référence de la littérature.En complément des techniques précédentes, nous avons également proposé des outils permettant de réduire la complexité de codeurs vidéo tels que VVC. La version actuelle du codeur VVC (VTM10) a un temps d'exécution neuf fois supérieur à celui du codeur HEVC. Par conséquent, le codeur VVC n'est pas adapté aux applications de codage et diffusion en temps réel sur les plateformes actuellement disponibles. Dans ce contexte, nous présentons une méthode systématique, de type branch-and-prune, permettant d'identifier un ensemble d'outils de codage pouvant être désactivés tout en satisfaisant une contrainte sur l'efficacité de codage. Ce travail contribue à la réalisation d'un codeur VVC temps réel
The acquisition and delivery of video content with minimal latency has become essential in several business areas such as sports broadcasting, video conferencing, telepresence, remote vehicle operation, or remote system control. The live streaming industry has grown in 2020 and it will expand further in the next few years with the emergence of new high-efficiency video codecs based on the Versatile Video Coding (VVC) standard and the fifth generation of mobile networks (5G).HTTP Adaptive Streaming (HAS) methods such as MPEG-DASH, using algorithms to adapt the transmission rate of compressed video, have proven to be very effective in improving the quality of experience (QoE) in a video-on-demand (VOD) context.Nevertheless, minimizing the delay between image acquisition and display at the receiver is essential in applications where latency is critical. Most rate adaptation algorithms are developed to optimize video transmission from a server situated in the core network to mobile clients. In applications requiring low-latency streaming, such as remote control of drones or broadcasting of sports events, the role of the server is played by a mobile terminal. The latter will acquire, compress, and transmit the video and transmit the compressed stream via a radio access channel to one or more clients. Therefore, client-driven rate adaptation approaches are unsuitable in this context because of the variability of the channel characteristics. In addition, HAS, for which the decision-making is done with a periodicity of the order of a second, are not sufficiently reactive when the server is moving, which may generate significant delays. It is therefore important to use a very fine adaptation granularity in order to reduce the end-to-end delay. The reduced size of the transmission and reception buffers (to minimize latency) makes it more difficult to adapt the throughput in our use case. When the bandwidth varies with a time constant smaller than the period with which the regulation is made, bad transmission rate decisions can induce a significant latency overhead.The aim of this thesis is to provide some answers to the problem of low-latency delivery of video acquired, compressed, and transmitted by mobile terminals. We first present a frame-by-frame rate adaptation algorithm for low latency broadcasting. A Model Predictive Control (MPC) approach is proposed to determine the coding rate of each frame to be transmitted. This approach uses information about the buffer level of the transmitter and about the characteristics of the transmission channel. Since the frames are coded live, a model relating the quantization parameter (QP) to the output rate of the video encoder is required. Hence, we have proposed a new model linking the rate to the QP of the current frame and to the distortion of the previous frame. This model provides much better results in the context of a frame-by-frame decision on the coding rate than the reference models in the literature.In addition to the above techniques, we have also proposed tools to reduce the complexity of video encoders such as VVC. The current version of the VVC encoder (VTM10) has an execution time nine times higher than that of the HEVC encoder. Therefore, the VVC encoder is not suitable for real-time encoding and streaming applications on currently available platforms. In this context, we present a systematic branch-and-prune method to identify a set of coding tools that can be disabled while satisfying a constraint on coding efficiency. This work contributes to the realization of a real-time VVC coder
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Books on the topic "Versatile Video Coding"

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Saldanha, Mário, Gustavo Sanchez, César Marcon, and Luciano Agostini. Versatile Video Coding (VVC). Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-11640-7.

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Rao, K. R., and Humberto Ochoa Dominguez. Versatile Video Coding. River Publishers, 2022.

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Versatile Video Coding. River Publishers, 2019.

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Rao, K. R., and Humberto Ochoa Dominguez. Versatile Video Coding. River Publishers, 2019.

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Rao, K. R., and Humberto Ochoa Dominguez. Versatile Video Coding. River Publishers, 2022.

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Rao, K. R., and Humberto Ochoa Dominguez. Versatile Video Coding. River Publishers, 2022.

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Saldanha, Mário, Gustavo Sanchez, Luciano Agostini, and César Marcon. Versatile Video Coding: Machine Learning and Heuristics. Springer International Publishing AG, 2022.

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Book chapters on the topic "Versatile Video Coding"

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Domínguez, Humberto Ochoa, and K. R. Rao. "Screen Content Coding for HEVC." In Versatile Video Coding, 139–51. New York: River Publishers, 2022. http://dx.doi.org/10.1201/9781003339991-4.

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Domínguez, Humberto Ochoa, and K. R. Rao. "Lossless and Visually Lossless Coding Algorithms." In Versatile Video Coding, 153–80. New York: River Publishers, 2022. http://dx.doi.org/10.1201/9781003339991-5.

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Domínguez, Humberto Ochoa, and K. R. Rao. "HEVC Encoder." In Versatile Video Coding, 19–137. New York: River Publishers, 2022. http://dx.doi.org/10.1201/9781003339991-3.

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Domínguez, Humberto Ochoa, and K. R. Rao. "Introduction." In Versatile Video Coding, 1. New York: River Publishers, 2022. http://dx.doi.org/10.1201/9781003339991-1.

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Domínguez, Humberto Ochoa, and K. R. Rao. "Beyond High Efficiency Video Coding (HEVC)." In Versatile Video Coding, 3–18. New York: River Publishers, 2022. http://dx.doi.org/10.1201/9781003339991-2.

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Saldanha, Mário, Gustavo Sanchez, César Marcon, and Luciano Agostini. "Versatile Video Coding (VVC)." In Versatile Video Coding (VVC), 7–22. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-11640-7_2.

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Saldanha, Mário, Gustavo Sanchez, César Marcon, and Luciano Agostini. "Learning-Based Fast Decision for Intra-frame Prediction Mode Selection for Luminance." In Versatile Video Coding (VVC), 89–97. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-11640-7_8.

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Saldanha, Mário, Gustavo Sanchez, César Marcon, and Luciano Agostini. "State-of-the-Art Overview." In Versatile Video Coding (VVC), 35–42. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-11640-7_4.

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Saldanha, Mário, Gustavo Sanchez, César Marcon, and Luciano Agostini. "Light Gradient Boosting Machine Configurable Fast Block Partitioning for Luminance." In Versatile Video Coding (VVC), 71–88. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-11640-7_7.

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Saldanha, Mário, Gustavo Sanchez, César Marcon, and Luciano Agostini. "Performance Analysis of VVC Intra-frame Prediction." In Versatile Video Coding (VVC), 43–61. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-11640-7_5.

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Conference papers on the topic "Versatile Video Coding"

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Sullivan, Gary. "Versatile Video Coding (VVC) Arrives." In 2020 IEEE International Conference on Visual Communications and Image Processing (VCIP). IEEE, 2020. http://dx.doi.org/10.1109/vcip49819.2020.9301847.

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Kulupana, Gosala, Venkata Phani Kumar M, and Saverio Blasi. "Fast Versatile Video Coding using Specialised Decision Trees." In 2021 Picture Coding Symposium (PCS). IEEE, 2021. http://dx.doi.org/10.1109/pcs50896.2021.9477461.

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Wien, Mathias, and Benjamin Bross. "Versatile Video Coding – Algorithms and Specification." In 2020 IEEE International Conference on Visual Communications and Image Processing (VCIP). IEEE, 2020. http://dx.doi.org/10.1109/vcip49819.2020.9301820.

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Li, Yiming, Zizheng Liu, Zhenzhong Chen, and Shan Liu. "Rate Control For Versatile Video Coding." In 2020 IEEE International Conference on Image Processing (ICIP). IEEE, 2020. http://dx.doi.org/10.1109/icip40778.2020.9191125.

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Cerveira, Arthur, Luciano Agostini, Bruno Zatt, and Felipe Sampaio. "Memory Assessment Of Versatile Video Coding." In 2020 IEEE International Conference on Image Processing (ICIP). IEEE, 2020. http://dx.doi.org/10.1109/icip40778.2020.9191358.

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Blaser, Max, Han Gao, Semih Esenlik, Elena Alshina, Zhijie Zhao, Christian Rohlfing, and Eckehard Steinbach. "Low-Complexity Geometric Inter-Prediction for Versatile Video Coding." In 2019 Picture Coding Symposium (PCS). IEEE, 2019. http://dx.doi.org/10.1109/pcs48520.2019.8954504.

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Xu, Xiaozhong, Xiang Li, and Shan Liu. "Current Picture Referencing in Versatile Video Coding." In 2019 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR). IEEE, 2019. http://dx.doi.org/10.1109/mipr.2019.00013.

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Li, Congrui, Zhenghui Zhao, Junru Li, Xiang Zhang, Siwei Ma, and Chen Li. "Bi-Intra Prediction for Versatile Video Coding." In 2019 Data Compression Conference (DCC). IEEE, 2019. http://dx.doi.org/10.1109/dcc.2019.00099.

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Chang, Tsui-Shan, Yu-Chen Sun, Ling Zhu, and Jian Lou. "Adaptive Resolution Change for Versatile Video Coding." In 2020 IEEE International Conference on Visual Communications and Image Processing (VCIP). IEEE, 2020. http://dx.doi.org/10.1109/vcip49819.2020.9301762.

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10

Gudumasu, Srinivas, Saurav Bandyopadhyay, and Yong He. "Software-based versatile video coding decoder parallelization." In MMSys '20: 11th ACM Multimedia Systems Conference. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3339825.3391871.

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Reports on the topic "Versatile Video Coding"

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Zhao, S., S. Wenger, Y. Sanchez, Y. K. Wang, and M. M Hannuksela. RTP Payload Format for Versatile Video Coding (VVC). RFC Editor, December 2022. http://dx.doi.org/10.17487/rfc9328.

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