{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T17:46:11Z","timestamp":1777657571264,"version":"3.51.4"},"reference-count":49,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"French Defense Procurement Agency"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. on Image Process."],"published-print":{"date-parts":[[2020]]},"DOI":"10.1109\/tip.2019.2934565","type":"journal-article","created":{"date-parts":[[2019,8,16]],"date-time":"2019-08-16T19:45:50Z","timestamp":1565984750000},"page":"679-693","source":"Crossref","is-referenced-by-count":54,"title":["Context-Adaptive Neural Network-Based Prediction for Image Compression"],"prefix":"10.1109","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7751-5219","authenticated-orcid":false,"given":"Thierry","family":"Dumas","sequence":"first","affiliation":[]},{"given":"Aline","family":"Roumy","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1604-967X","authenticated-orcid":false,"given":"Christine","family":"Guillemot","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1162\/NECO_a_00052"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref33","first-page":"670","article-title":"Video frame interpolation via adaptive convolution","author":"niklaus","year":"2017","journal-title":"Proc CVPR"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298747"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.77"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2644615"},{"key":"ref37","first-page":"249","article-title":"Understanding the difficulty of training deep feedforward neural networks","volume":"9","author":"glorot","year":"2010","journal-title":"J Mach Learn Res"},{"key":"ref36","first-page":"1","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2015","journal-title":"Proc ICLR"},{"key":"ref35","first-page":"437","article-title":"Practical recommendations for gradient-based training of deep architectures","author":"bengio","year":"2013","journal-title":"Neural Networks Tricks of the Trade"},{"key":"ref34","article-title":"Frame interpolation with multi-scale deep loss functions and generative adversarial networks","author":"van amersfoort","year":"2017","journal-title":"arXiv 1711 06045"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2439281"},{"key":"ref27","year":"2017","journal-title":"Kodak Lossless True Color Image Suite"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2017.151"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2012.2221525"},{"key":"ref1","author":"wien","year":"2014","journal-title":"High Efficiency Video Coding Coding Tools and Specification"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1126\/science.1127647"},{"key":"ref22","first-page":"1","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2014","journal-title":"Proc ICLR"},{"key":"ref21","first-page":"1","article-title":"Using very deep autoencoders for content-based image retrieval","author":"krizhevsky","year":"2011","journal-title":"Proc ESANN"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.278"},{"key":"ref23","first-page":"1","article-title":"Rectifier nonlinearities improve neural network acoustic models","author":"maas","year":"2013","journal-title":"Proc ICML"},{"key":"ref26","article-title":"A guide to convolution arithmetic for deep learning","author":"dumoulin","year":"2018","journal-title":"ArXiv 1603 07285"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.178"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2011.2170700"},{"key":"ref11","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1561\/2000000010","article-title":"Source coding: Part I of fundamentals of source and video coding","volume":"4","author":"wiegand","year":"2011","journal-title":"Found Trends Signal Process"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2012.6248110"},{"key":"ref12","first-page":"1927","article-title":"Generative image modeling using spatial LSTMs","author":"theis","year":"2015","journal-title":"Proc NIPS"},{"key":"ref13","first-page":"1","article-title":"Pixel recurrent neural networks","author":"van der oord","year":"2016","journal-title":"Proc ICML"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2817044"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/18.720541"},{"key":"ref16","article-title":"Video (language) modeling: A baseline for generative models of natural videos","author":"ranzato","year":"2015","journal-title":"arXiv 1412 6604"},{"key":"ref17","first-page":"1","article-title":"Deep multi-scale video prediction beyond mean square error","author":"mathieu","year":"2015","journal-title":"Proc ICLR"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-49430-8_2"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1098\/rspb.1998.0303"},{"key":"ref3","first-page":"831","article-title":"Edges are the ‘independent components’ of natural scenes","author":"bell","year":"1996","journal-title":"Proc NIPS"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.5152-14.2015"},{"key":"ref5","first-page":"873","article-title":"Sparse deep belief net model for visual area V2","author":"lee","year":"2007","journal-title":"Proc NIPS"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.29"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/1553374.1553453"},{"key":"ref49","author":"rosewarne","year":"2014","journal-title":"Common Test Conditions and Software Reference Configurations for HEVC Range Extensions"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2006.312685"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/IPAS.2016.7880122"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.12988\/ams.2014.49750"},{"key":"ref48","article-title":"Calculation of average PSNR differences between RD-curves","author":"bjontegaard","year":"2001"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2012.2221191"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref41","first-page":"1097","article-title":"ImageNet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc NIPS"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-88682-2_24"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2001.937655"}],"container-title":["IEEE Transactions on Image Processing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/83\/8835130\/08804361.pdf?arnumber=8804361","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T14:39:08Z","timestamp":1651070348000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8804361\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"references-count":49,"URL":"https:\/\/doi.org\/10.1109\/tip.2019.2934565","relation":{},"ISSN":["1057-7149","1941-0042"],"issn-type":[{"value":"1057-7149","type":"print"},{"value":"1941-0042","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]}}}