{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T15:29:07Z","timestamp":1777994947157,"version":"3.51.4"},"reference-count":98,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"}],"funder":[{"name":"Guangdong NSF Project","award":["2018B030312002"],"award-info":[{"award-number":["2018B030312002"]}]},{"name":"Research Projects of Zhejiang Lab","award":["2019KD0AB03"],"award-info":[{"award-number":["2019KD0AB03"]}]},{"name":"Guangzhou Research Project","award":["201902010037"],"award-info":[{"award-number":["201902010037"]}]},{"name":"Key-Area Research and Development Program of Guangzhou","award":["202007030004"],"award-info":[{"award-number":["202007030004"]}]},{"DOI":"10.13039\/501100016022","name":"Data Center of Management Science National Natural Science Foundation of China - Peking University","doi-asserted-by":"publisher","award":["62076260"],"award-info":[{"award-number":["62076260"]}],"id":[{"id":"10.13039\/501100016022","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100016022","name":"Data Center of Management Science National Natural Science Foundation of China - Peking University","doi-asserted-by":"publisher","award":["U1811461"],"award-info":[{"award-number":["U1811461"]}],"id":[{"id":"10.13039\/501100016022","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100016022","name":"Data Center of Management Science National Natural Science Foundation of China - Peking University","doi-asserted-by":"publisher","award":["U1911401"],"award-info":[{"award-number":["U1911401"]}],"id":[{"id":"10.13039\/501100016022","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Pattern Anal. Mach. Intell."],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/tpami.2021.3058679","type":"journal-article","created":{"date-parts":[[2021,2,13]],"date-time":"2021-02-13T02:19:13Z","timestamp":1613182753000},"page":"1-1","source":"Crossref","is-referenced-by-count":17,"title":["APANet: Auto-Path Aggregation for Future Instance Segmentation Prediction"],"prefix":"10.1109","author":[{"given":"Jian-Fang","family":"Hu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiangxin","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zihang","family":"Lin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jian-Huang","family":"Lai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenjun","family":"Zeng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei-Shi","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.77"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01240-3_36"},{"key":"ref3","article-title":"DARTS: Differentiable architecture search","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Liu"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.350"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.400"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00271"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2699184"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00913"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1909.11065"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00326"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00064"},{"key":"ref12","article-title":"Ocnet: Object context network for scene parsing","author":"Yuan","year":"2018"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00690"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.660"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1802.02611"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00388"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00770"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2572683"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2644615"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.106"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/s11280-018-0556-3"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00254"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00858"},{"key":"ref25","article-title":"STFCN: spatio-temporal FCN for semantic video segmentation","author":"Fayyaz","year":"2016"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-018-1130-2"},{"key":"ref27","article-title":"Interactive video object segmentation via spatio-temporal context aggregation and online learning","volume-title":"Proc. DAVIS Challenge Video Object Segmentation - CVPR Workshops","author":"Lin"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00147"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00699"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2844175"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00215"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01221"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1145\/1291233.1291310"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2775623"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00904"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.100"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.305"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.774"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.378"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.343"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.472"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00657"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00511"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2577031"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00925"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58523-5_38"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00860"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00933"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58452-8_17"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00745"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58607-2_31"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00856"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00915"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01024"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10584-0_20"},{"key":"ref56","first-page":"1990","article-title":"Learning to segment object candidates","volume-title":"Proc. Advances Neural Inf. Process. Syst.","author":"Pinheiro"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46448-0_5"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46466-4_32"},{"key":"ref59","article-title":"Deep multi-scale video prediction beyond mean square error","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Mathieu"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00191"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01270-0_46"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00910"},{"key":"ref63","first-page":"2863","article-title":"Action-conditional video prediction using deep networks in atari games","volume-title":"Proc. Advances Neural Inf. Process. Syst.","author":"Oh"},{"key":"ref64","first-page":"879","article-title":"PredRNN: Recurrent neural networks for predictive learning using spatiotemporal LSTMs","volume-title":"Proc. Advances Neural Inf. Process. Syst.","author":"Wang"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1145\/3123266.3123349"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2011.64"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00441"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01249-6_19"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.18"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2728788"},{"key":"ref71","article-title":"Future semantic segmentation with convolutional LSTM","author":"Rochan","year":"2018"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2020.2992184"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-33676-9_13"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00907"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33014780"},{"key":"ref76","first-page":"8699","article-title":"Searching for efficient multi-scale architectures for dense image prediction","volume-title":"Proc. Advances Neural Inf. Process. Syst.","author":"Chen"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00017"},{"key":"ref78","article-title":"Designing neural network architectures using reinforcement learning","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Baker"},{"key":"ref79","doi-asserted-by":"publisher","DOI":"10.1145\/3071178.3071229"},{"key":"ref80","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11709"},{"key":"ref81","article-title":"Simple and efficient architecture search for convolutional neural networks","author":"Elsken","year":"2017"},{"key":"ref82","article-title":"Neural architecture search with reinforcement learning","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Zoph"},{"key":"ref83","first-page":"2902","article-title":"Large-scale evolution of image classifiers","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Real"},{"key":"ref84","article-title":"Accelerating neural architecture search using performance prediction","author":"Baker","year":"2017"},{"key":"ref85","first-page":"4092","article-title":"Efficient neural architecture search via parameter sharing","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Pham"},{"key":"ref86","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00257"},{"key":"ref87","first-page":"550","article-title":"Understanding and simplifying one-shot architecture search","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Bender"},{"key":"ref88","first-page":"2016","article-title":"Neural architecture search with Bayesian optimisation and optimal transport","volume-title":"Proc. Advances Neural Inf. Process. Syst.","author":"Kandasamy"},{"key":"ref89","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330648"},{"key":"ref90","first-page":"500","article-title":"Deep neural architecture search with deep graph Bayesian optimization","volume-title":"Proc. IEEE\/WIC\/ACM Int. Conf. Web Intell.","author":"Ma"},{"key":"ref91","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01246-5_2"},{"key":"ref92","article-title":"Efficient multi-objective neural architecture search via lamarckian evolution","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Elsken"},{"key":"ref93","article-title":"Proxylessnas: Direct neural architecture search on target task and hardware","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Cai"},{"key":"ref94","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3350949"},{"key":"ref95","first-page":"802","article-title":"Convolutional LSTM network: A machine learning approach for precipitation nowcasting","volume-title":"Proc. Advances Neural Inf. Process. Syst.","author":"Shi"},{"key":"ref96","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01252-6_44"},{"key":"ref97","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10602-1_48"},{"key":"ref98","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2014.2369050"}],"container-title":["IEEE Transactions on Pattern Analysis and Machine Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/34\/4359286\/09353241.pdf?arnumber=9353241","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,9]],"date-time":"2024-01-09T23:08:21Z","timestamp":1704841701000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9353241\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":98,"URL":"https:\/\/doi.org\/10.1109\/tpami.2021.3058679","relation":{},"ISSN":["0162-8828","2160-9292","1939-3539"],"issn-type":[{"value":"0162-8828","type":"print"},{"value":"2160-9292","type":"electronic"},{"value":"1939-3539","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}