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Systems and Networking related Video research published in major venues of Computer Science.
https://github.com/SINR-Group/Video-Lit

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Systems and Networking related Video research published in major venues of Computer Science.

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# VideoLiterature

Literature of video streaming research published in major venues such as SIGCOMM, NSDI, MobiCom, MobiSys, IMC, CoNEXT, INFOCOM, MM, MMSys, OSDI, SOSP etc.



## Video Streaming

* [Swift: Adaptive Video Streaming with Layered Neural Codecs](https://www3.cs.stonybrook.edu/~mdasari/papers/nsdi-2022-paper.pdf) [NSDI'22]

* [SenSei: Aligning Video Streaming Quality with Dynamic User Sensitivity](https://www.usenix.org/system/files/nsdi21-zhang.pdf) [NSDI'21]

* [Learning in situ: a randomized experiment in video streaming](https://arxiv.org/pdf/1906.01113.pdf) [NSDI'20]

* [Grad: Learning for Overhead-aware Adaptive Video Streaming with Scalable Video Coding](http://jhc.sjtu.edu.cn/~bjiang/papers/Liu_MM2020_Grad.pdf) [MM'20]

* [PERM: Neural Adaptive Video Streaming with Multi-path Transmission]() [INFOCOM'20]

* [End-to-End Transport for Video QoE Fairness](http://web.cs.ucla.edu/~ravi/CS219_F19/papers/minerva.pdf) [SIGCOMM'19]

* [PiTree: Practical Implementation of ABR Algorithms Using Decision Trees]() [MM'19] [[Code](https://github.com/transys-project/pitree/)] [[Dataset](https://github.com/transys-project/pitree-dataset/)]

* [Requet: Real-Time QoE Detection for Encrypted YouTube Traffic](https://wimnet.ee.columbia.edu/wp-content/uploads/2019/02/MMsys19_Requet.pdf) [MMSys'19][[Data](https://github.com/Wimnet/RequetDataSet)]

* [Oboe: Auto-tuning Video ABR Algorithms to Network Conditions](https://engineering.purdue.edu/~isl/papers/sigcomm18-final128.pdf) [SIGCOMM'18]

* [Neural Adaptive Content-aware Internet Video Delivery](https://www.usenix.org/system/files/osdi18-yeo.pdf) [OSDI'18]

* [ABR Streaming of VBR-encoded Videos: Characterization, Challenges, and Solutions](https://www-users.cs.umn.edu/~fengqian/paper/vbr_conext18.pdf) [CoNEXT'18]

* [Understanding Video Management Planes](https://engineering.purdue.edu/~isl/papers/imc2018.pdf) [IMC'18]

* [From Theory to Practice: Improving Bitrate Adaptation in the DASH Reference Player](https://www.akamai.com/us/en/multimedia/documents/technical-publication/improving-bitrate-adaptation-in-the-dash-reference-player.pdf) [MMSys'18]

* [VideoNOC: assessing video QoE for network operators using passive measurements](https://www.cc.gatech.edu/~tmangla3/papers/VideoNOC_MMSys2018.pdf) [MMSys'18]

* [Disk|Crypt|Net: rethinking the stack for high-performance video streaming](https://www.cl.cam.ac.uk/~rnw24/papers/201708-sigcomm-diskcryptnet.pdf) [SIGCOMM'17]

* [Neural Adaptive Video Streaming with Pensieve](https://people.csail.mit.edu/hongzi/content/publications/Pensieve-Sigcomm17.pdf) [SIGCOMM'17][[Code](https://github.com/hongzimao/pensieve)]

* [Pytheas: Enabling Data-Driven QoE Optimization Using Group-Based Exploration-Exploitation](https://www.usenix.org/system/files/conference/nsdi17/nsdi17-jiang_0.pdf) [NSDI'17]

* [Dissecting VOD Services for Cellular: Performance, Root Causes and Best Practices](https://conferences.sigcomm.org/imc/2017/papers/imc17-final111.pdf) [IMC'17]

* [CS2P: Improving Video Bitrate Selection and Adaptation with Data-Driven Throughput Prediction](https://users.ece.cmu.edu/~vsekar/papers/sigcomm16_cs2p.pdf) [SIGCOMM'16]

* [MP-DASH: Adaptive Video Streaming Over Preference-Aware Multipath](http://www.research.att.com/ecms/dam/sites/labs_research/content/publications/VA_MP-DASH_Adaptive_Video_Streaming.pdf) [CoNEXT'16]

* [DASH2M: Exploring HTTP/2 for Internet Streaming to Mobile Devices](https://dl.acm.org/citation.cfm?id=2964313) [MM'16]

* [BOLA: Near-Optimal Bitrate Adaptation for Online Videos](https://arxiv.org/pdf/1601.06748.pdf) [INFOCOM'16]

* [A Control-Theoretic Approach for Dynamic Adaptive Video Streaming over HTTP](https://users.ece.cmu.edu/~vsekar/papers/sigcomm15_mpcdash.pdf) [SIGCOMM'15]

* [Can Accurate Predictions Improve Video Streaming in Cellular Networks?](http://www.cs.jhu.edu/~xinjin/files/HotMobile15_VideoStreaming.pdf) [HotMobile'15]

* [A Buffer-Based Approach to Rate Adaptation: Evidence from a Large Video Streaming Service](http://yuba.stanford.edu/~nickm/papers/sigcomm2014-video.pdf) [SIGCOMM'14]

* [Improving Fairness, Efficiency, and Stability in HTTP-based Adaptive Video Streaming with FESTIVE](https://conferences.sigcomm.org/co-next/2012/eproceedings/conext/p97.pdf) [CoNEXT'12]



## Volumetric Video

* [Split Rendering for Mixed Reality: Interactive Volumetric Video in Action](https://www.hhi.fraunhofer.de/fileadmin/PDF/VCA/MC/siggraphxr20.pdf) [SIGGRAPH ASIA'20 XR Demo]

* [LESSONS LEARNT DURING ONE YEAR OF COMMERCIAL VOLUMETRIC VIDEO PRODUCTION](https://www.ibc.org/download?ac=10506) [Technical Report]

* [GROOT: A Real-time Streaming System of High-Fidelity Volumetric Videos]() [MobiCom'20]

* [ViVo: Visibility-Aware Mobile Volumetric Video Streaming]() [MobiCom'20]



## Video Telephony

* [NEMO: Enabling Neural-enhanced Video Streaming on Commodity Mobile Devices]() [MobiCom'20]

* [OnRL: Improving Mobile Video Telephony via Online Reinforcement Learning]() [MobiCom'20]

* [LiveNAS - Neural-Enhanced Live Streaming: Improving Live Video Ingest via Online Learning]() [SIGCOMM'20]

* [Jigsaw: Robust Live 4K Video Streaming](http://www.cs.utexas.edu/~jianhe/jigsaw-mobicom19.pdf) [MobiCom'19]

* [Learning to Coordinate Video Codec with Transport Protocol for Mobile Video Telephony](https://dl.acm.org/citation.cfm?id=3345430) [MobiCom'19]

* [Vantage: optimizing video upload for time-shifted viewing of social live streams](https://dl.acm.org/citation.cfm?id=3342064) [SIGCOMM'19]

* [Salsify: Low-Latency Network Video Through Tighter Integration Between a Video Codec and a Transport Protocol](https://cs.stanford.edu/~keithw/salsify-paper.pdf) [NSDI'18]

* [Encoding, Fast and Slow: Low-Latency Video Processing Using Thousands of Tiny Threads](https://www.usenix.org/system/files/conference/nsdi17/nsdi17-fouladi.pdf) [NSDI'17]

* [POI360: Panoramic Mobile Video Telephony over LTE Cellular Networks](http://xyzhang.ucsd.edu/papers/XXie_CoNEXT17_POI360.pdf) [CoNEXT'17]



## 360 Degree Video

* [PARIMA: Viewport Adaptive 360-Degree Video Streaming](https://www.researchgate.net/publication/349704480_PARIMA_Viewport_Adaptive_360-Degree_Video_Streaming) [WWW'2021]

* [PARSEC: Streaming 360-degree Videos using Super-Resolution](https://www3.cs.stonybrook.edu/~mdasari/assets/pdf/infocom20.pdf) [INFOCOM'20] [[Code](https://github.com/VideoForage/Super-Resolution)]

* [Flocking-based Live Streaming of 360-degree Video](https://www.researchgate.net/publication/341703327_Flocking-based_live_streaming_of_360-degree_video) [MMSys'20]

* [ClusTile: Toward Minimizing Bandwidth in 360-degree Video Streaming](http://www.cs.binghamton.edu/~yaoliu/publications/infocom18-clustile.pdf) [INFOCOM'19]

* [Pano: Optimizing 360° Video Streaming with a Better Understanding of Quality Perception](https://people.cs.uchicago.edu/~junchenj/docs/360StreamingQuality_SIGCOMM.pdf) [SIGCOMM'19]

* [Flare: Practical Viewport-Adaptive 360-Degree Video Streaming for Mobile Devices](https://www-users.cs.umn.edu/~fengqian/paper/flare_mobicom18.pdf) [Mobicom'18]

* [Rubiks: Practical 360-Degree Streaming for Smartphones](http://www.cs.utexas.edu/~jianhe/rubiks_mobisys.pdf) [Mobisys'18]

* [CLS: A Cross-user Learning based System for Improving QoE in 360-degree Video Adaptive Streaming](https://dl.acm.org/citation.cfm?id=3240556) [MM'18]

* [Favor: Fine-Grained Video Rate Adaptation](https://www.cs.utexas.edu/~mubashir/papers/favor_mmsys.pdf) [MMSys'18]

* [BAS-360: Exploring Spatial and Temporal Adaptability in 360-degree Videos over HTTP/2](http://www.cs.binghamton.edu/~yaoliu/publications/infocom18-bas360.pdf) [INFOCOM'18]

* [Dynamic Adaptive Streaming for Multi-Viewpoint Omnidirectional Videos](https://ir.cwi.nl/pub/27893/27893.pdf) [MMSys'18]

* [An HTTP/2-Based Adaptive Streaming Framework for 360° Virtual Reality Videos](https://biblio.ugent.be/publication/8541796/file/8541800.pdf) [MM'17]

* [360ProbDASH: Improving QoE of 360 Video Streaming Using Tile-based HTTP Adaptive Streaming](https://dl.acm.org/citation.cfm?id=3123266.3123291) [MM'17]

* [OpTile: Toward Optimal Tiling in 360-degree Video Streaming](http://www.cs.binghamton.edu/~yaoliu/publications/mm17-optile.pdf) [MM'17]

* [It’s All Around You: Exploring 360° Video iewing Experiences on Mobile Devices](http://www.fahim-kawsar.net/papers/Broeck.MM2017-Camera.pdf) [MM'17]

* [Adaptive 360-Degree Video Streaming using Scalable Video Coding](https://www.utdallas.edu/~afshin/publication/360.pdf) [MM'17]

* [A Measurement Study of Oculus 360 Degree Video Streaming](http://www.greenorbs.org/people/lzh/papers/[MMSys'17]%20360%20Video.pdf) [MMSys'17]

* [Optimal Set of 360-Degree Videos for Viewport-Adaptive Streaming](https://dl.acm.org/citation.cfm?id=3123372) [MM'17]



## Architectural Support for Video Streaming

* [Warehouse-Scale Video Acceleration: Co-design and Deployment in the Wild](https://www.gwern.net/docs/cs/2021-ranganathan.pdf) [ASPLOS'21]

* [Deja View: Spatio-Temporal Compute Reuse for Energy-Efficient 360° VR Video Streaming](https://conferences.computer.org/isca/pdfs/ISCA2020-4QlDegUf3fKiwUXfV0KdCm/466100a241/466100a241.pdf) [ISCA '20]

* [Distilling the Essence of Raw Video to Reduce Memory Usage and Energy at Edge Devices](https://dl.acm.org/doi/10.1145/3352460.3358298) [MICRO '19]

* [Race-To-Sleep + Content Caching + Display Caching: A Recipe for Energy-eficient Video Streaming on Handhelds](https://dl.acm.org/doi/10.1145/3123939.3123948) [MICRO '17]



## Video Analytics

* [Enabling Edge-Cloud Video Analytics for Robotic Applications](https://www.cse.ust.hk/~ywanggf/public/files/runespoor-infocom21.pdf) [INFOCOM'21]

* [Server-Driven Video Streaming for Deep Learning Inference](https://people.cs.uchicago.edu/~junchenj/docs/DDS-Sigcomm20.pdf) [SIGCOMM'20]

* [Reducto: On-Camera Filtering for Resource-Efficient Real-Time Video Analytics](http://web.cs.ucla.edu/~harryxu/papers/li-sigcomm20.pdf) [SIGCOMM'20]

* [Scaling Video Analytics on Constrained Edge Nodes](https://hyeontaek.com/papers/ff-sysml2019.pdf) [SysML'19]

* [AWStream: adaptive wide-area streaming analytics](https://awstream.github.io/paper/awstream.pdf) [SIGCOMM'18]

* [Chameleon: Scalable Adaptation of Video Analytics](http://people.cs.uchicago.edu/~junchenj/docs/Chameleon_SIGCOMM_CameraReady.pdf) [SIGCOMM'18]

* [Focus: Querying Large Video Datasets with Low Latency and Low Cost](https://www.usenix.org/system/files/osdi18-hsieh.pdf) [OSDI'18]



## Video Classification

* [YouTube-8M: A Large-Scale Video Classification

Benchmark](https://arxiv.org/pdf/1609.08675.pdf)[arxiv'16]

* [Beyond Short Snippets: Deep Networks for Video Classification](https://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Ng_Beyond_Short_Snippets_2015_CVPR_paper.pdf) [CVPR'15]

* [Large-scale Video Classification with Convolutional Neural Networks](https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/42455.pdf) [CVPR'14]



## Video Streaming using Layered Video Coding

* [Grad: Learning for Overhead-aware Adaptive Video Streaming with Scalable Video Coding](http://jhc.sjtu.edu.cn/~bjiang/papers/Liu_MM2020_Grad.pdf) [ACM MM'20]

* [LBP: Robust Rate Adaptation Algorithm for SVC Video Streaming](https://arxiv.org/pdf/1805.00041.pdf) [IEEE/ACM ToN'19]

* [Layer-Assisted Adaptive Video Streaming](https://dl.acm.org/doi/pdf/10.1145/3210445.3210454) [ACM NOSSDAV'18]



## Layered Video Coding

* [Layered Coding vs. Multiple Descriptions for Video Streaming over Multiple Paths](https://web.stanford.edu/~bgirod/pdfs/ChakareskiACM03.pdf) [ACM MM'03]

* [Two-Layer Coding of Video Signals for VBR Networks](https://web.stanford.edu/~bgirod/pdfs/ChakareskiACM03.pdf) [IEEE JSAC'1989]

* [Multiple Description Coding](https://github.com/mdasari823/Multiple-Description-Coding)



## Video Coding with Deep Learning

* [Efficient Video Compression via Content-Adaptive Super-Resolution](https://openaccess.thecvf.com/content/ICCV2021/papers/Khani_Efficient_Video_Compression_via_Content-Adaptive_Super-Resolution_ICCV_2021_paper.pdf) [ICCV'21] [[Code](https://github.com/AdaptiveVC/SRVC)]

* [Online-trained Upsampler for Deep Low Complexity Video Compression](https://openaccess.thecvf.com/content/ICCV2021/papers/Klopp_Online-Trained_Upsampler_for_Deep_Low_Complexity_Video_Compression_ICCV_2021_paper.pdf) [ICCV'21]

* [ELF-VC: Efficient Learned Flexible-Rate Video Coding](https://arxiv.org/pdf/2104.14335.pdf) [arxiv'21]

* [Learning for Video Compression with Hierarchical Quality and Recurrent Enhancement](https://arxiv.org/pdf/2003.01966.pdf) [CVPR'20]

* [Learned Video Compression](https://arxiv.org/pdf/1811.06981.pdf) [ICCV'19]

* [DVC: An End-to-end Deep Video Compression Framework](https://github.com/GuoLusjtu/DVC) [CVPR'19]

* [Deep Learning-Based Video Coding: A Review and A Case Study](https://arxiv.org/pdf/1904.12462.pdf) [arxiv'19]

* [Video Compression through Image Interpolation](https://www.philkr.net/papers/2018-09-02-eccv/2018-09-02-eccv.pdf) [ECCV'18][[Code](https://github.com/chaoyuaw/pytorch-vcii)]



## Saliency-aware Video Coding

* [Revisiting Video Saliency: A Large-scale Benchmark and a New Model](https://zpascal.net/cvpr2018/Wang_Revisiting_Video_Saliency_CVPR_2018_paper.pdf) [CVPR'18]

* [A semiautomatic saliency model and its application to video compression](http://compression.ru/video/savam/pdf/A_semiautomatic_saliency_model_and_its_application_to_video_compression_ICCP_2017_0.pdf) [ICCP'17]



## VR/AR

* [Towards Retina-Quality VR Video Streaming: 15 ms Could Save You 80% of Your Bandwidth](https://arxiv.org/pdf/2108.12720.pdf) [Arxive'21]

* [Edge Assisted Real-time Object Detection for Mobile Augmented Reality](http://www.winlab.rutgers.edu/~luyang/papers/mobicom19_augmented_reality.pdf) [MobiCom'19]

* [Cutting the Cord: Designing a High-quality Untethered VR System with Low Latency Remote Rendering](http://www.winlab.rutgers.edu/~gruteser/papers/mobisys18_low_latency_vr.pdf) [MobiSys'18]

* [Creating the Perfect Illusion : What will it take to Create Life-Like Virtual Reality Headsets?](https://www.microsoft.com/en-us/research/uploads/prod/2018/05/perfectillusion.pdf) [HotMobile'18]

* [Furion: Engineering High-Quality Immersive Virtual Reality on Today’s Mobile Devices](http://www.yongcui.org/lunwen/Furion.pdf) [MobiCom'17]

* [HEVC-compliant Tile-based Streaming of Panoramic Video for Virtual Reality Applications](https://dl.acm.org/citation.cfm?id=2967292) [MM'16]



## 3D Video Streaming in the Early Days

* [Packetization Interval of Haptic Media in Networked Virtual Environments](https://dl.acm.org/doi/pdf/10.1145/1103599.1103625?casa_token=a0SmS8nytnAAAAAA:MLUUQr4eBc2341SMwJEewfCYQh2L7WfjyG-leD4FxalMfe0QtKGNdnWKKqLHE6OS2gpe9z-NVwv9Fg) [NetGames'05]

* [OpenPING: A Reflective Middleware for the Construction of Adaptive Networked Game Applications](https://dl.acm.org/doi/pdf/10.1145/1016540.1016548?casa_token=4KZprKt__scAAAAA:9mpnI3Vd-TQ7U-RPdXnQmeKUkkZvvH829Cpjh4OSKJUofnSdAoMMhZE8lnDveiQQvUPQAI_g45g9Bw) [ACM SIGCOMM Workshops'04]

* [Scalable Peer-to-Peer Networked Virtual Environment](https://dl.acm.org/doi/pdf/10.1145/1016540.1016552?casa_token=dWTmlxqx1ZYAAAAA:E7SwHpIJbUP0Dyp6YsQmXCAP1ld8S1soal0rQqGUz4Z5E4N7vupO9TF5oKYATTm9tDSU6K9zRNIi1w) [ACM SIGCOMM Workshops'04]

* [Real-Time Streaming of Point-Based 3D Video](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=1310060&casa_token=1jQtTa8i6toAAAAA:gCap-HdAQTNk0sDb1yPmcCJ6_iUvseX5h6Mkhh65QV4fb3utZZwYFNYsAr6ve6ZgcJ-Z3Yfu-Q&tag=1) [IEEE VR'04]

* [The Metaverse: a networked collection of inexpensive, self-configuring, immersive environments](http://diglib.eg.org/handle/10.2312/EGVE.IPT_EGVE2003.115-124) [ACM EuroGraphics Workshop'03]

* [ATM network impairment valuation of an experimental 3D videophone for virtual reality telecommunication system](https://ieeexplore.ieee.org/document/997286) [IEEE ICC'02]

* [Beyond Audio and Video: Multimedia Networking Support for Distributed, lmmersive Virtual Environments](https://ieeexplore.ieee.org/document/952468) [IEEE EuroMicro'01]

* [Virtual reality telecommunication system-a person to person multimedia communication system](https://ieeexplore.ieee.org/abstract/document/891853) [IEEE Globecom'00]

* [Virtual reality movies-real-time streaming of 3D objects](https://www.sciencedirect.com/science/article/pii/S1389128699000973?casa_token=YQhjsVjXOuoAAAAA:OUchkRQiJNtEcLfw7hqVB_1XZ1H1K4Ugbg2G5zN4WY2_usTG2sYjRNt_8_qTnvjtSmY7WhzALkM) [Elsevier Computer Networks'99]

* [A Distributed 3D Graphics Library](http://www.cs.columbia.edu/~bm/siggraph98.pdf) [ACM SIGGRAPH'98]

* [The DIVEBONE - An Application-Level Network Architecture for Internet-Based CVEs](https://dl.acm.org/doi/pdf/10.1145/323663.323672) [ACM VRST'99]

* [DWTP—an Internet protocol for shared virtual environments](https://dl.acm.org/doi/10.1145/271897.274370) [ACM Web3D VRML Workshop'98]

* [Adaptive _ Distributed Multimedia: A Concept for haracterising Co-cognitive Virtual Reality Systems](http://repository.ias.ac.in/85183/1/47-p.pdf) [IEEE INFOCOM'92]



## Video Streaming in the Early Days

* [The Feasibility of Supporting Large-Scale Live Streaming Applications with Dynamic Application End-Points](https://www.conviva.com/wp-content/uploads/2017/09/the-feasability-of-supporting-live-streaming-with-dynamic-application-endpoints.pdf) [SIGCOMM'04]

* [An Analysis of Live Streaming Workloads on the Internet](https://www.akamai.com/content/dam/site/en/documents/research-paper/an-analysis-of-live-streaming-workloads-on-the-internet-technical-publication.pdf) [IMC'04]

* [Measurement Study of Low-bitrate Internet Video Streaming](https://www.land.ufrj.br/laboratory/repository/upfiles/inproceedings/meas-low-bit-video.pdf) [IMC'01]

* [An Empirical Study of RealVideo Performance Across the Internet](https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.118.6973&rep=rep1&type=pdf) [IMC'01]

* [Analysis, Modeling and Generation of Self-Similar VBR Video Traffic](http://www.cs.kent.edu/~xzou/NetProj/Ref/040124164326272342.pdf) [SIGCOMM'1994]

* [On buffer requirements for store-and-forward video on demand service circuits](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=188525) [GLOBECOM'1991]

* [Video On Demand: Is It Feasible?](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=116506) [GLOBECOM'1990]

* [Video on Demand: A Wideband Service or Myth?](https://www.semanticscholar.org/paper/Video-on-Demand%3A-A-Wideband-Service-or-Myth-Judice-Addeo/ced4fa8baa5dd935aae67a9b352a7b6e637b6c00) [ICC'1986]



## Journals

* [A Survey on Bitrate Adaptation Schemes for Streaming Media over HTTP](https://www.comp.nus.edu.sg/~bentaleb/files/papers/journal/ABRSurvey.pdf) [IEEE Communications Surveys & Tutorials'18]



# Tools

Following are the tools and libraries that are useful to build your ideas on top of.

## Multimedia Libraries

* [FFMPEG](https://ffmpeg.org/): A multimedia library with a collection of diverse video codecs, filters, and video streaming capabilities.

* [GPAC](https://github.com/gpac/gpac): A multimedia library that has decoding, rendering and displaying support. It also has support for 360 degree video delivery. It comes with MP4Box to package the video into DASH format segments and MP4Client a video player with adaptive video streaming solutions

* [x265](https://github.com/videolan/x265): Open source implementation H.265 video codec.

* [OBS Studio](https://obsproject.com/): Open source broadcaster software. It is useful to stream live videos on platforms such as Facebook and Periscope etc.

* [SVT Encoders](https://github.com/OpenVisualCloud): Software (multithreaded CPU) implementation of HEVC, VP9 and AV1 encoders.

* [Saliency-aware Video Codec](https://github.com/msu-video-group/x264_saliency_mod): X264 implementation of saliency-aware video compression.

* [SHVC](https://hevc.hhi.fraunhofer.de/shvc): Layered coding - scalable extentions for H.265/HEVC

* [SVC](https://avc.hhi.fraunhofer.de/svc): Layered coding - scalable extensions for H.264/AVC

* [VVC](https://jvet.hhi.fraunhofer.de/): Reference implementation of H.266/VVC 

* [Open3DGC](https://github.com/KhronosGroup/glTF/wiki/Open-3D-Graphics-Compression): Mesh compression library from Khronos Group



## Datasets

* [360-Degree Video Dataset](https://github.com/360VidStr/A-large-dataset-of-360-video-user-behaviour): A comprehensive 360-degree video dataset (88 videos) with user behavior.