{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T02:23:43Z","timestamp":1730255023288,"version":"3.28.0"},"reference-count":49,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,8,21]],"date-time":"2022-08-21T00:00:00Z","timestamp":1661040000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,8,21]],"date-time":"2022-08-21T00:00:00Z","timestamp":1661040000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,8,21]]},"DOI":"10.1109\/icpr56361.2022.9956375","type":"proceedings-article","created":{"date-parts":[[2022,11,29]],"date-time":"2022-11-29T14:34:13Z","timestamp":1669732453000},"page":"1-8","source":"Crossref","is-referenced-by-count":0,"title":["Borrowing from yourself: Faster future video segmentation with partial channel update"],"prefix":"10.1109","author":[{"given":"Evann","family":"Courdier","sequence":"first","affiliation":[{"name":"EPFL,Idiap Research Institute"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Francois","family":"Fleuret","sequence":"additional","affiliation":[{"name":"University of Geneva,Idiap Research Institute"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ICME.2019.00280"},{"article-title":"Future semantic segmentation with convolutional lstm","year":"2018","author":"rochan","key":"ref38"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00405"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00365"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00959"},{"article-title":"Deep dual-resolution networks for real-time and accurate semantic segmentation of road scenes","year":"2021","author":"hong","key":"ref30"},{"article-title":"Bayesian prediction of future street scenes using synthetic likelihoods","year":"2018","author":"bhattacharyya","key":"ref37"},{"article-title":"Future semantic segmentation using 3d structure","year":"2018","author":"vora","key":"ref36"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.77"},{"key":"ref34","article-title":"Real-time segmentation networks should be latency aware","author":"courdier","year":"2020","journal-title":"Proceedings of the Asian Conference on Computer Vision"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00884"},{"article-title":"Bisenet v2: Bilateral network with guided aggregation for real-time semantic segmentation","year":"2020","author":"yu","key":"ref27"},{"article-title":"Rethink dilated convolution for real-time semantic segmentation","year":"2021","author":"gao","key":"ref29"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00628"},{"key":"ref1","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-319-49409-8_69","article-title":"Clockwork Convnets for Video Semantic Segmentation","author":"shelhamer","year":"2016"},{"article-title":"Lawin transformer: Improving semantic segmentation transformer with multi-scale representations via large window attention","year":"2022","author":"yan","key":"ref20"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00717"},{"article-title":"Fully transformer networks for semantic image segmentation","year":"2021","author":"wu","key":"ref21"},{"article-title":"ICNet for Real-Time Semantic Segmentation on High-Resolution Images","year":"2017","author":"zhao","key":"ref24"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00975"},{"key":"ref26","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-030-01261-8_20","article-title":"BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation","author":"yu","year":"2018"},{"article-title":"Enet: A deep neural network architecture for real-time semantic segmentation","year":"2016","author":"paszke","key":"ref25"},{"article-title":"Mobilenets: Efficient convolutional neural networks for mobile vision applications","year":"2017","author":"howard","key":"ref10"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"},{"article-title":"Spatio-temporal video autoencoder with differentiable memory","year":"2015","author":"patraucean","key":"ref40"},{"key":"ref12","first-page":"234","article-title":"U-net: Convolutional networks for biomedical image segmentation","author":"ronneberger","year":"2015","journal-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2644615"},{"key":"ref14","doi-asserted-by":"crossref","first-page":"1904","DOI":"10.1109\/TPAMI.2015.2389824","article-title":"Spatial pyramid pooling in deep convolutional networks for visual recognition","volume":"37","author":"he","year":"2015","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"article-title":"Pyramid Scene Parsing Network (PSPNet)","year":"2016","author":"zhao","key":"ref15"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.75"},{"key":"ref17","doi-asserted-by":"crossref","first-page":"834","DOI":"10.1109\/TPAMI.2017.2699184","article-title":"Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs","volume":"40","author":"chen","year":"2017","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"article-title":"Segformer: Simple and efficient design for semantic segmentation with transformers","year":"2021","author":"xie","key":"ref18"},{"key":"ref19","article-title":"Segmentation transformer: Object-contextual representations for semantic segmentation","volume":"1","author":"yuan","year":"2021","journal-title":"European Conference on Computer Vision (ECCV)"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00272"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00239"},{"key":"ref6","first-page":"12607","article-title":"In defense of pre-trained imagenet architectures for real-time semantic segmentation of roaddriving images","author":"orsic","year":"2019","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.350"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58452-8_45"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00189"},{"key":"ref9","first-page":"801","article-title":"Encoderdecoder with atrous separable convolution for semantic image segmentation","author":"chen","year":"2018","journal-title":"Proceedings of the European Conference on Computer Vision (ECCV)"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01240-3_36"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01066"},{"article-title":"Slimmable neural networks","year":"2018","author":"yu","key":"ref48"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2020.2992184"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.477"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.441"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2019.00186"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00713"}],"event":{"name":"2022 26th International Conference on Pattern Recognition (ICPR)","start":{"date-parts":[[2022,8,21]]},"location":"Montreal, QC, Canada","end":{"date-parts":[[2022,8,25]]}},"container-title":["2022 26th International Conference on Pattern Recognition (ICPR)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9956007\/9955631\/09956375.pdf?arnumber=9956375","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,19]],"date-time":"2022-12-19T15:07:16Z","timestamp":1671462436000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9956375\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,21]]},"references-count":49,"URL":"https:\/\/doi.org\/10.1109\/icpr56361.2022.9956375","relation":{},"subject":[],"published":{"date-parts":[[2022,8,21]]}}}