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2023 Data Compression Conference (DCC)最新文献

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Decoder-side Affine Model Refinement for Video Coding beyond VVC 解码器侧仿射模型改进的视频编码超越VVC
2023 Data Compression Conference (DCC) Pub Date : 2023-03-01 DOI: 10.1109/DCC55655.2023.00033
Jing Chen, Ru-Ling Liao, Yan Ye, Xinwei Li
{"title":"Decoder-side Affine Model Refinement for Video Coding beyond VVC","authors":"Jing Chen, Ru-Ling Liao, Yan Ye, Xinwei Li","doi":"10.1109/DCC55655.2023.00033","DOIUrl":"https://doi.org/10.1109/DCC55655.2023.00033","url":null,"abstract":"Decoder-side motion vector refinement (DMVR) was adopted into versatile video coding (VVC) and later was further improved in the enhance compression model (ECM) to improve the inter prediction accuracy by refining the motion vectors (MVs) derived from previously coded blocks in merge mode based on bilateral matching. However, DMVR can only be applied to blocks coded with translational motion. Affine motion compensation as supported by VVC can capture more complex motion and thus increases inter prediction accuracy, but DMVR is not applied to blocks coded with affine motion in VVC. In this paper, it is proposed to refine the affine model for affine merge coded blocks at the decoder side. The proposed method includes two steps, of which the first step refines the base MV and the second step refines the non-translation parameters. Experimental results show that by only applying base MV refinement, the proposed method achieves overall {0.15% (Y), 0.06% (U), 0.11% (V)} Bjontegaard delta bit-rate (BD-rate) reduction, and by applying both base MV and non-translation parameter refinement, the proposed method achieves overall {0.27% (Y), 0.15% (U), 0.19% (V)} BD-rate reduction in random access (RA) configuration. Due to the good trade-off between performance and complexity, the base MV refinement was adopted in ECM-7.0 and non-translation parameter refinement is currently being studied in exploration experiments (EE).","PeriodicalId":209029,"journal":{"name":"2023 Data Compression Conference (DCC)","volume":"265 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133360834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Practical construction of sensing matrices for a greedy sparse recovery algorithm over finite fields 有限域上贪婪稀疏恢复算法感知矩阵的实际构造
2023 Data Compression Conference (DCC) Pub Date : 2023-03-01 DOI: 10.1109/DCC55655.2023.00020
Mégane Gammoudi, Christian Scheunert, Giang T. Nguyen, F. Fitzek
{"title":"Practical construction of sensing matrices for a greedy sparse recovery algorithm over finite fields","authors":"Mégane Gammoudi, Christian Scheunert, Giang T. Nguyen, F. Fitzek","doi":"10.1109/DCC55655.2023.00020","DOIUrl":"https://doi.org/10.1109/DCC55655.2023.00020","url":null,"abstract":"Compressed sensing aims to retrieve sparse signals from very few samples. It relies on dedicated reconstruction algorithms and well-chosen measurement matrices. In combination with network coding, which operates traditionally over finite fields, it leverages the benefits of both techniques. However, compressed sensing has been primarily investigated over the real field. F2OMP is one of the few recovery algorithms to reconstruct signals over finite fields. However, its use in practical cases is limited since its performance depends mainly on binary matrices for signal recovery. This paper reports results of extensive simulations enhancing the features of well-performing measurement matrices for F2OMP as well as methods to build them. Moreover, a modified version of the algorithm, F2OMP-loop, is proposed. It offers a compromise between performance, stability, and processing time. This allows to design a joint compressed sensing and network coding framework over finite fields.","PeriodicalId":209029,"journal":{"name":"2023 Data Compression Conference (DCC)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133826628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
MacSR: Macroblock-aware Lightweight Video Super-Resolution MacSR:支持宏块的轻量级视频超分辨率
2023 Data Compression Conference (DCC) Pub Date : 2023-03-01 DOI: 10.1109/DCC55655.2023.00061
Rui He, Qing Li, Qian Yu, Zhenhui Yuan, Wanxin Shi, Jianhui Lv, Yi Han
{"title":"MacSR: Macroblock-aware Lightweight Video Super-Resolution","authors":"Rui He, Qing Li, Qian Yu, Zhenhui Yuan, Wanxin Shi, Jianhui Lv, Yi Han","doi":"10.1109/DCC55655.2023.00061","DOIUrl":"https://doi.org/10.1109/DCC55655.2023.00061","url":null,"abstract":"SummaryThe mobile video quality can be improved by video super-resolution (SR) especially when bandwidth is limited. To achieve real-time SR, the latest work, ClassSR (CVPR 19), divides frames into equal-size image blocks (IBs), and different-complexity SR models are used respectively to reduce the computational burden.","PeriodicalId":209029,"journal":{"name":"2023 Data Compression Conference (DCC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115045468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Multiscale convolutional neural networks for in-loop video restoration 多尺度卷积神经网络在循环视频恢复中的应用
2023 Data Compression Conference (DCC) Pub Date : 2023-03-01 DOI: 10.1109/DCC55655.2023.00027
K. Misra, A. Segall, Byeongdoo Choi
{"title":"Multiscale convolutional neural networks for in-loop video restoration","authors":"K. Misra, A. Segall, Byeongdoo Choi","doi":"10.1109/DCC55655.2023.00027","DOIUrl":"https://doi.org/10.1109/DCC55655.2023.00027","url":null,"abstract":"Incorporating neural networks into a video codec as an in-loop filter has been shown to provide significant improvements in coding efficiency. Unfortunately, the computational complexity associated with the neural network, specifically the number of multiply-accumulate (MAC) operations, makes these approaches intractable in practice. In this paper, we consider using a multiscale approach to reduce complexity while maintaining coding efficiency. Experimental results demonstrate a 5.4× reduction in MAC operations while achieving an average bit rate savings of 6.4% and 6.3% for all intra and random access coding, respectively, when compared to the evolving AV2 standard. Ablation studies are also provided and show that the approach achieves all but 0.2% of the coding efficiency of full resolution processing.","PeriodicalId":209029,"journal":{"name":"2023 Data Compression Conference (DCC)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114806166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Improving Compression Efficiency using an Encoder-aware Motion Compensated Temporal Filter 利用编码器感知的运动补偿时间滤波器提高压缩效率
2023 Data Compression Conference (DCC) Pub Date : 2023-03-01 DOI: 10.1109/dcc55655.2023.00085
R. Vanam, S. Sethuraman
{"title":"Improving Compression Efficiency using an Encoder-aware Motion Compensated Temporal Filter","authors":"R. Vanam, S. Sethuraman","doi":"10.1109/dcc55655.2023.00085","DOIUrl":"https://doi.org/10.1109/dcc55655.2023.00085","url":null,"abstract":"Motion Compensated Temporal Filtering (MCTF) is a pre-processing approach employed prior to video encoding, for improving the compression efficiency. Prior MCTF designs (e.g. [1]) use pre-defined frame-level quantization parameters (QPs) for different slice types and temporal layers, and operate with a fixed Group of Pictures (GOP) structure. However, commercial encoders can adapt GOP structure based upon content characteristics, and can also adapt QPs on a block-basis based upon the frequency of the block being referenced and the spatial complexity of the block, causing prior MCTF to perform sub-optimally with commercial encoders.","PeriodicalId":209029,"journal":{"name":"2023 Data Compression Conference (DCC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117197857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
LZ4r - A New Fast Compression Algorithm for High-Speed Data Storage Systems 高速数据存储系统中一种新的快速压缩算法LZ4r
2023 Data Compression Conference (DCC) Pub Date : 2023-03-01 DOI: 10.1109/DCC55655.2023.00051
Rui Chen, Lihao Xu
{"title":"LZ4r - A New Fast Compression Algorithm for High-Speed Data Storage Systems","authors":"Rui Chen, Lihao Xu","doi":"10.1109/DCC55655.2023.00051","DOIUrl":"https://doi.org/10.1109/DCC55655.2023.00051","url":null,"abstract":"LZ4 data compression algorithm is the current state-of-art compression algorithm in the high speed compression algorithm class, and has been adopted and integrated by lots modern high-speed data storage systems. We propose a fast lossless compression algorithm, named LZ4r. A new format of the data sequence is designed, and by integrating it into the proposed algorithm, a better compression ratio than LZ4 is achieved. Numerous evaluation tests are conducted with different sets of data corpus. The results consistently show that LZ4r gains a significant improvement in compression ratio than LZ4, with a similar high compression speed. Although LZ4r is slower than LZ4 in decompression speed, the decompression speed of LZ4r is still fast enough not to reduce the overall performance of the system. Thus, LZ4r can become a practical and competitive alternative or replacement of LZ4 in many high-speed data storage systems to improve the overall performance and lower the overall cost. More details about LZ4r algorithm design and performance evaluation can be found at [1].","PeriodicalId":209029,"journal":{"name":"2023 Data Compression Conference (DCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130041660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Measuring the Similarity of Files by Data Compression 基于数据压缩的文件相似性度量
2023 Data Compression Conference (DCC) Pub Date : 2023-03-01 DOI: 10.1109/DCC55655.2023.00063
Hubert Schölnast
{"title":"Measuring the Similarity of Files by Data Compression","authors":"Hubert Schölnast","doi":"10.1109/DCC55655.2023.00063","DOIUrl":"https://doi.org/10.1109/DCC55655.2023.00063","url":null,"abstract":"The two meta-algorithms Concat Compress and Cross Compress, which can be used to measure the similarity of files, were subjected to an extensive practical test together with the compression algorithms Re-Pair, gzip and bz2:Five labeled datasets with 6533 entries and approximately 10 MB were subjected to a classification procedure using these algorithms. Theoretical considerations of the two meta-algorithms have been made in the past [1], but the practical implementation of these methods is still in its infancy. The results from our experiments are promising and show the great potential of this approach.","PeriodicalId":209029,"journal":{"name":"2023 Data Compression Conference (DCC)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125847738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Hierarchical Privacy-Preserving and Communication-Efficient Compression via Compressed Sensing 基于压缩感知的分层隐私保护和通信高效压缩
2023 Data Compression Conference (DCC) Pub Date : 2023-03-01 DOI: 10.1109/DCC55655.2023.00078
Hui Huang, Di Xiao, Mengdi Wang
{"title":"Hierarchical Privacy-Preserving and Communication-Efficient Compression via Compressed Sensing","authors":"Hui Huang, Di Xiao, Mengdi Wang","doi":"10.1109/DCC55655.2023.00078","DOIUrl":"https://doi.org/10.1109/DCC55655.2023.00078","url":null,"abstract":"Data collection and sharing have a tremendous impact on technology, business and society. Correspondingly, it brings in significant privacy and communication concerns. To this end, we present a hierarchical privacy-preserving and communication-efficient compression scheme via compressed sensing (CS) to address these two issues. In the encoding stage, the obfuscated sensitive regions and non-sensitive regions are compressed and encrypted simultaneously. Consequently, the semi-authorized users and authorized users are considered in the decoding stage. Additionally, the left annihilator matrices provide various kinds of recovery qualities for real-world requirements, which further achieves communication-efficient compression.","PeriodicalId":209029,"journal":{"name":"2023 Data Compression Conference (DCC)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116953599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Compressing the Trees of Canonical Binary AIFV Coding 压缩规范二值AIFV编码树
2023 Data Compression Conference (DCC) Pub Date : 2023-03-01 DOI: 10.1109/DCC55655.2023.00050
Qi Cheng, Sian-Jheng Lin, Nenghai Yu
{"title":"Compressing the Trees of Canonical Binary AIFV Coding","authors":"Qi Cheng, Sian-Jheng Lin, Nenghai Yu","doi":"10.1109/DCC55655.2023.00050","DOIUrl":"https://doi.org/10.1109/DCC55655.2023.00050","url":null,"abstract":"Canonical binary AIFV coding [1] contains two trees T<inf>0</inf> and T<inf>1</inf>. We show the method to compress T<inf>0</inf>, and the method to compress T<inf>1</inf> is with a similar way. We provide a new method to store the number of leaves, master nodes and complete internal nodes in each layer and compactly encode the string of numbers according to the specific property between the nodes.","PeriodicalId":209029,"journal":{"name":"2023 Data Compression Conference (DCC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121411196","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
On the future of decoder-side depth estimation in MPEG immersive video coding 解码器侧深度估计在MPEG沉浸式视频编码中的应用前景
2023 Data Compression Conference (DCC) Pub Date : 2023-03-01 DOI: 10.1109/DCC55655.2023.00042
Dawid Mieloch, A. Dziembowski, J. Jeong, Gwangsoon Lee
{"title":"On the future of decoder-side depth estimation in MPEG immersive video coding","authors":"Dawid Mieloch, A. Dziembowski, J. Jeong, Gwangsoon Lee","doi":"10.1109/DCC55655.2023.00042","DOIUrl":"https://doi.org/10.1109/DCC55655.2023.00042","url":null,"abstract":"The paper presents a new profile of the MPEG immersive video (MIV) coding standard, developed to cover diverse use cases based on the decoder-side depth estimation (DSDE) and allow for further improvements of future MIV ed.2.","PeriodicalId":209029,"journal":{"name":"2023 Data Compression Conference (DCC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128530375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
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