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Surv."],"published-print":{"date-parts":[[2021,1,31]]},"abstract":"<jats:p>The past decade has witnessed the great success of deep learning in many disciplines, especially in computer vision and image processing. However, deep learning-based video coding remains in its infancy. We review the representative works about using deep learning for image\/video coding, an actively developing research area since 2015. We divide the related works into two categories: new coding schemes that are built primarily upon deep networks, and deep network-based coding tools that shall be used within traditional coding schemes. For deep schemes, pixel probability modeling and auto-encoder are the two approaches, that can be viewed as predictive coding and transform coding, respectively. For deep tools, there have been several techniques using deep learning to perform intra-picture prediction, inter-picture prediction, cross-channel prediction, probability distribution prediction, transform, post- or in-loop filtering, down- and up-sampling, as well as encoding optimizations. In the hope of advocating the research of deep learning-based video coding, we present a case study of our developed prototype video codec, Deep Learning Video Coding (DLVC). DLVC features two deep tools that are both based on convolutional neural network (CNN), namely CNN-based in-loop filter and CNN-based block adaptive resolution coding. The source code of DLVC has been released for future research.<\/jats:p>","DOI":"10.1145\/3368405","type":"journal-article","created":{"date-parts":[[2020,2,6]],"date-time":"2020-02-06T21:54:04Z","timestamp":1581026044000},"page":"1-35","update-policy":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":136,"title":["Deep Learning-Based Video Coding"],"prefix":"10.1145","volume":"53","author":[{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0001-9100-2906","authenticated-orcid":false,"given":"Dong","family":"Liu","sequence":"first","affiliation":[{"name":"CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System, University of Science and Technology of China, Hefei, Anhui Province, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yue","family":"Li","sequence":"additional","affiliation":[{"name":"CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System, University of Science and Technology of China, Hefei, Anhui Province, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianping","family":"Lin","sequence":"additional","affiliation":[{"name":"CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System, University of Science and Technology of China, Hefei, Anhui Province, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Houqiang","family":"Li","sequence":"additional","affiliation":[{"name":"CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System, University of Science and Technology of China, Hefei, Anhui Province, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Feng","family":"Wu","sequence":"additional","affiliation":[{"name":"CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System, University of Science and Technology of China, Hefei, Anhui Province, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2020,2,6]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2018.2878952"},{"key":"e_1_2_1_2_1","unstructured":"Eirikur Agustsson Fabian Mentzer Michael Tschannen Lukas Cavigelli Radu Timofte Luca Benini and Luc Van Gool. 2017. 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