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Partition-Aware Adaptive Switching Neural Networks for Post-Processing in HEVC

Weiyao Lin, Xiaoyi He, Xintong Han, Dong Liu, John See, Junni Zou, Hongkai Xiong, Feng Wu
2019 IEEE transactions on multimedia  
We first propose a partition-aware Convolution Neural Network (CNN) that utilizes the partition information produced by the encoder to assist in the post-processing.  ...  This paper addresses neural network based post-processing for the state-of-the-art video coding standard, High Efficiency Video Coding (HEVC).  ...  CNNs in the adaptive-switching neural network.  ... 
doi:10.1109/tmm.2019.2962310 fatcat:t4qibru325btrapfui6nn5oxru

Image and Video Compression with Neural Networks: A Review

Siwei Ma, Xinfeng Zhang, Chuanmin Jia, Zhenghui Zhao, Shiqi Wang, Shanshe Wanga
2019 IEEE transactions on circuits and systems for video technology (Print)  
Deep convolution neural network (CNN) which makes the neural network resurge in recent years and has achieved great success in both artificial intelligent and signal processing fields, also provides a  ...  The evolution and development of neural network based compression methodologies are introduced for images and video respectively.  ...  adaptive switching for compression task.  ... 
doi:10.1109/tcsvt.2019.2910119 fatcat:ibwmmewdlfcexjxfetsxzga52y

A CNN-based Prediction-Aware Quality Enhancement Framework for VVC

Fatemeh Nasiri, Wassim Hamidouche, Luce Morin, Nicolas Dhollande, Gildas Cocherel
2021 IEEE Open Journal of Signal Processing  
This paper presents a framework for Convolutional Neural Network (CNN)-based quality enhancement task, by taking advantage of coding information in the compressed video signal.  ...  In addition to the Post Processing (PP) approach, the In-Loop Filtering (ILF) codec integration has also been considered, where the characteristics of the Group of Pictures (GoP) are taken into account  ...  For instance, if the device is equipped with dedicated Graphic Processing Unit (GPU) or other neural network inference hardware, then the post-processing can be applied and bring quality improvement at  ... 
doi:10.1109/ojsp.2021.3092598 fatcat:dqgzponwuza7taqsjalo36rgby

A Comprehensive Benchmark for Single Image Compression Artifacts Reduction [article]

Jiaying Liu, Dong Liu, Wenhan Yang, Sifeng Xia, Xiaoshuai Zhang, Yuanying Dai
2019 arXiv   pre-print
Compression artifacts removal, as a common post-processing technique, aims at alleviating undesirable artifacts such as blockiness, ringing, and banding caused by quantization and approximation in the  ...  In this work, a systematic listing of the reviewed methods is presented based on their basic models (handcrafted models and deep networks).  ...  [38] proposed a residual highway convolutional neural network (RHCNN) for in-loop filter of HEVC.  ... 
arXiv:1909.03647v1 fatcat:yujaixpevzeadi7zfh7ap6t7jq

2020 Index IEEE Transactions on Multimedia Vol. 22

2020 IEEE transactions on multimedia  
., +, TMM Feb. 2020 421-431 Partition-Aware Adaptive Switching Neural Networks for Post-Processing in HEVC.  ...  ., +, TMM July 2020 1667-1679 Learning Local Quality-Aware Structures of Salient Regions for Stereoscopic Images via Deep Neural Networks.  ...  Image watermarking Blind Watermarking for 3-D Printed Objects by Locally Modifying Layer Thickness. 2780 -2791 Low-Light Image Enhancement With Semi-Decoupled Decomposition.  ... 
doi:10.1109/tmm.2020.3047236 fatcat:llha6qbaandfvkhrzpe5gek6mq

Networked VR: State of the Art, Solutions, and Challenges

Jinjia Ruan, Dongliang Xie
2021 Electronics  
Therefore, simply providing high bandwidth is insufficient in compensating for this difference, because the demands for scale and supply vary widely.  ...  In addition to a thorough summary of recent progress, we also present an outlook of future developments in the quality of immersive experience networks and unified data set measurement in VR video transmission  ...  An appropriate QoE model can help video providers to determine how to partition and encode 360-degree video and provide a benchmark for network operators to design QoE-aware scheduling algorithms.  ... 
doi:10.3390/electronics10020166 fatcat:s2hmmr6dqrcztkft2r7uqmnq44

Measuring, modelling and Integrating Time-varying Video Quality in End-to-End Multimedia Service Delivery: A Review and Open Challenges

Chaminda T.E.R. Hewage, Arslan Ahmad, Thanuja Mallikarachchi, Nabajeet Barman, Maria G. Martini
2022 IEEE Access  
state-of-the-art for QoE modelling, QoE-aware encoding/decoding and QoE monitoring/management of multimedia streaming in next-generation networks.  ...  The multimedia delivery chain consists of multiple stages such as content preparation, content delivery via Over-The-Top delivery network and Internet Service Providers network.  ...  Standards Standardization Purpose Body MPEG-DASH ISO For Content delivery in HTTP adaptive [19] video streaming SAND [112] ISO For server and network-aware content delivery in HTTP adaptive video stream  ... 
doi:10.1109/access.2022.3180491 fatcat:4mcyfjfd2zhrzl7qytj7vwkwsm

Machine Learning for Multimedia Communications

Nikolaos Thomos, Thomas Maugey, Laura Toni
2022 Sensors  
Machine learning is revolutionizing the way multimedia information is processed and transmitted to users.  ...  For example, the high model capacity of the learning-based architectures enables us to accurately model the image and video behavior such that tremendous compression gains can be achieved.  ...  , segmentation, post-processing, and so forth (as illustrated in Figure 8 ).  ... 
doi:10.3390/s22030819 pmid:35161566 pmcid:PMC8840624 fatcat:nmz7s6ei3bdddarbt2bqhf6beu

360-Degree Video Streaming: A Survey of the State of the Art

Rabia Shafi, Wan Shuai, Muhammad Usman Younus
2020 Symmetry  
360-degree video streaming is expected to grow as the next disruptive innovation due to the ultra-high network bandwidth (60–100 Mbps for 6k streaming), ultra-high storage capacity, and ultra-high computation  ...  Finally, some significant research challenges and implications in the immersive multimedia environment are presented and explained in detail.  ...  M.U.Y. helps in writing manuscript and proofread the manuscript. All authors have read and agreed to the published version of the manuscript.  ... 
doi:10.3390/sym12091491 fatcat:wciqpwsi75grffl2ug73uzsbsm

How to Exploit the Transferability of Learned Image Compression to Conventional Codecs [article]

Jan P. Klopp, Keng-Chi Liu, Liang-Gee Chen, Shao-Yi Chien
2021 arXiv   pre-print
However, convolutional neural network based algorithms have a large computational footprint.  ...  As a possible avenue to this goal, in this work, we propose and investigate how learned image coding can be used as a surrogate to optimize an image for encoding.  ...  networks in the image formation process.  ... 
arXiv:2012.01874v2 fatcat:ch2tul3onfflzdv44ayk55wem4

A Study of the Evolution of Video Codec and its Future Research Direction

Anitha Kumari R. D., Narendranath Udupa
2020 2020 Third International Conference on Advances in Electronics, Computers and Communications (ICAECC)  
The underlying principle of video compression is methodically subject to optimizing the data required for the storage, transmission, and processing of video streaming applications without compromising  ...  compression has become widely adopted prominent technology among bandwidth-hungry mobile streaming applications, where the prime aim is to reduce the redundant features from the video frame sequence, which in  ...  neural networks (CNN) to evolve up for better compression outcome with highefficiency predictive coding with learning scenario.  ... 
doi:10.1109/icaecc50550.2020.9339513 fatcat:hntn6pcgtzbkxmd6x5e3qeu5eu

Table of contents

2021 ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)  
-1: SIGNAL PROCESSING FOR NETWORKS SPCOM-1.1: DATA-DRIVEN ADAPTIVE NETWORK RESOURCE SLICING FOR ........................................... 4715 MULTI-TENANT NETWORKS Navid Reyhanian, University of Minnesota  ...  China, China MLSP-48: NEURAL NETWORK APPLICATIONS MLSP-48.1: TASK-AWARE NEURAL ARCHITECTURE SEARCH .................................................................. 3025 Cat Le, Mohammadreza Soltani,  ... 
doi:10.1109/icassp39728.2021.9414617 fatcat:m5ugnnuk7nacbd6jr6gv2lsfby

A survey on video streaming in multipath and multihomed overlay networks

Ali Ali Hodroj, Marc Ibrahim, Yassine Hadjadj-Aoul
2021 IEEE Access  
The focus of this survey is to study the protocols, mechanisms, and the latest standards proposed in the literature for improving the performance and quality of video content in multipath and multihomed  ...  overlay networks.  ...  It consists of using Spatial Relationship Description (SRD) to realize dynamic viewport-aware adaptation technique based on the user's viewing viewport where the highest quality is assigned for tiles in  ... 
doi:10.1109/access.2021.3076464 fatcat:bql3hvmxenesvawb72xilv3qkm

Deep Generative Adversarial Compression Artifact Removal [article]

Leonardo Galteri, Lorenzo Seidenari, Marco Bertini, Alberto Del Bimbo
2017 arXiv   pre-print
Moreover we show that our approach can be used as a pre-processing step for object detection in case images are degraded by compression to a point that state-of-the art detectors fail.  ...  In this task, our GAN method obtains better performance than MSE or SSIM trained networks.  ...  Acknowledgments We gratefully acknowledge the support of NVIDIA Corporation with the donation of the Titan X Pascal GPU used for this research.  ... 
arXiv:1704.02518v3 fatcat:qfaktt6evja5fbjcm2aj23g6fm

Deep Generative Adversarial Compression Artifact Removal

Leonardo Galteri, Lorenzo Seidenari, Marco Bertini, Alberto Del Bimbo
2017 2017 IEEE International Conference on Computer Vision (ICCV)  
Moreover we show that our approach can be used as a pre-processing step for object detection in case images are degraded by compression to a point that state-of-the art detectors fail.  ...  In this task, our GAN method obtains better performance than MSE or SSIM trained networks.  ...  In this work we address the problem of artifact removal using convolutional neural networks.  ... 
doi:10.1109/iccv.2017.517 dblp:conf/iccv/GalteriSBB17 fatcat:dnfhpntvlrgodkosbhvf47jqpu
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