{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T11:04:33Z","timestamp":1783595073207,"version":"3.55.0"},"reference-count":28,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,10,16]],"date-time":"2022-10-16T00:00:00Z","timestamp":1665878400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,10,16]],"date-time":"2022-10-16T00:00:00Z","timestamp":1665878400000},"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":[[2022,10,16]]},"DOI":"10.1109\/icip46576.2022.9897774","type":"proceedings-article","created":{"date-parts":[[2022,11,3]],"date-time":"2022-11-03T21:27:24Z","timestamp":1667510844000},"page":"16-20","source":"Crossref","is-referenced-by-count":16,"title":["Hypergraph Convolutional Networks for Weakly-Supervised Semantic Segmentation"],"prefix":"10.1109","author":[{"given":"Jhony H.","family":"Giraldo","sequence":"first","affiliation":[{"name":"La Rochelle Université,Laboratoire Mathématiques, Image et Applications (MIA),France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vincenzo","family":"Scarrica","sequence":"additional","affiliation":[{"name":"Università di Napoli Parthenope,Dipartimento di Scienze e Tecnologie,Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Antonino","family":"Staiano","sequence":"additional","affiliation":[{"name":"Università di Napoli Parthenope,Dipartimento di Scienze e Tecnologie,Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francesco","family":"Camastra","sequence":"additional","affiliation":[{"name":"Università di Napoli Parthenope,Dipartimento di Scienze e Tecnologie,Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thierry","family":"Bouwmans","sequence":"additional","affiliation":[{"name":"La Rochelle Université,Laboratoire Mathématiques, Image et Applications (MIA),France"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","article-title":"U-Net: Con-volutional networks for biomedical image segmentation","volume-title":"MICCAI","author":"Ronneberger"},{"key":"ref2","article-title":"Deep-GCNs: Can GCNs go as deep as CNNs?","volume-title":"IEEE ICCV","author":"Li"},{"key":"ref3","article-title":"Graph moving object segmentation","author":"Giraldo","year":"2020","journal-title":"IEEE T-PAMI"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2644615"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2699184"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP40778.2020.9190887"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1093\/nsr\/nwx106"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2016.7532562"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.344"},{"key":"ref11","article-title":"Graph-Net: Learning image pseudo annotations for weakly-supervised semantic segmentation","volume-title":"ACM Multimedia","author":"Pu"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3083269"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2020.107637"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2012.120"},{"key":"ref15","article-title":"Very deep convolutional networks for large-scale image recognition","volume-title":"ICLR","author":"Simonyan"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01234-2_49"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-014-0733-5"},{"key":"ref18","article-title":"Semi-supervised classification with graph convolutional networks","volume-title":"ICLR","author":"Kipf"},{"key":"ref19","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","volume-title":"ICML","author":"Ioffe"},{"key":"ref20","article-title":"Fast and accurate deep network learning by exponential linear units (ELUs)","volume-title":"ICLR","author":"Clevert"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11604"},{"key":"ref23","article-title":"Iterative deep graph learning for graph neural networks: Better and robust node embeddings","volume-title":"NeurIPS","author":"Chen"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2011.6126343"},{"key":"ref25","article-title":"Adam: A method for stochastic optimization","volume-title":"ICLR","author":"Kingma"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00195"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.315"},{"key":"ref28","article-title":"Efficient inference in fully connected CRFs with Gussian edge potentials","volume-title":"NeurIPS","author":"Kr\u00e4henb\u00fchl"}],"event":{"name":"2022 IEEE International Conference on Image Processing (ICIP)","location":"Bordeaux, France","start":{"date-parts":[[2022,10,16]]},"end":{"date-parts":[[2022,10,19]]}},"container-title":["2022 IEEE International Conference on Image Processing (ICIP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9897158\/9897159\/09897774.pdf?arnumber=9897774","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,22]],"date-time":"2024-01-22T21:23:01Z","timestamp":1705958581000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9897774\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,16]]},"references-count":28,"URL":"https:\/\/doi.org\/10.1109\/icip46576.2022.9897774","relation":{},"subject":[],"published":{"date-parts":[[2022,10,16]]}}}