{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T09:46:43Z","timestamp":1762508803239,"version":"3.28.0"},"reference-count":38,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,5,23]],"date-time":"2022-05-23T00:00:00Z","timestamp":1653264000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,5,23]],"date-time":"2022-05-23T00:00:00Z","timestamp":1653264000000},"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":[[2022,5,23]]},"DOI":"10.1109\/icra46639.2022.9811601","type":"proceedings-article","created":{"date-parts":[[2022,7,12]],"date-time":"2022-07-12T19:36:40Z","timestamp":1657654600000},"page":"742-748","source":"Crossref","is-referenced-by-count":16,"title":["Learning Object Relations with Graph Neural Networks for Target-Driven Grasping in Dense Clutter"],"prefix":"10.1109","author":[{"given":"Xibai","family":"Lou","sequence":"first","affiliation":[{"name":"Univ. of Minnesota,Department of Electrical and Computer Engineering,Minneapolis,USA"}]},{"given":"Yang","family":"Yang","sequence":"additional","affiliation":[{"name":"Univ. of Minnesota,Department of Computer Science and Engineering,Minneapolis,USA"}]},{"given":"Changhyun","family":"Choi","sequence":"additional","affiliation":[{"name":"Univ. of Minnesota,Department of Electrical and Computer Engineering,Minneapolis,USA"}]}],"member":"263","reference":[{"key":"ref38","first-page":"510","article-title":"The ycb object and model set: Towards common benchmarks for manipulation research","author":"calli","year":"0","journal-title":"Advanced Robotics (ICAR) 2015 international conference on IEEE"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2017.8206060"},{"key":"ref32","first-page":"1912","article-title":"3d shapenets: A deep representation for volumetric shapes","author":"wu","year":"0","journal-title":"2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.586"},{"journal-title":"ShapeNet An Information-Rich 3D Model Repository","year":"2015","author":"chang","key":"ref30"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1145\/37401.37422"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2012.6225337"},{"journal-title":"DeeperGCN All You Need to Train Deeper GCNs","year":"2020","author":"li","key":"ref35"},{"key":"ref34","article-title":"The best of both modes: Separately leveraging rgb and depth for unseen object instance segmentation","author":"xie","year":"0","journal-title":"Conference on Robot Learning (CoRL)"},{"key":"ref10","article-title":"Semi-Supervised Classification with Graph Convolutional Networks","author":"kipf","year":"0","journal-title":"Proceedings of the 5th International Conference on Learning Representations ser"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.robot.2011.07.016"},{"key":"ref12","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1109\/TRO.2013.2289018","article-title":"Data-driven grasp synthesis—a survey","volume":"30","author":"bohg","year":"2013","journal-title":"IEEE Transactions on Robotics"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1177\/0278364914549607"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2016.7487517"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2018.8593986"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48506.2021.9561737"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48506.2021.9561139"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2016.7759114"},{"key":"ref19","doi-asserted-by":"crossref","first-page":"1455","DOI":"10.1177\/0278364917735594","article-title":"Grasp pose detection in point clouds","volume":"36","author":"ten pas","year":"2017","journal-title":"The International Journal of Robotics Research"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33017370"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"ref27","article-title":"Graph attention networks","author":"velickovic","year":"2017","journal-title":"ArXiv Preprint"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA40945.2020.9197318"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.aiopen.2021.01.001"},{"key":"ref29","first-page":"8459","article-title":"Learning to simulate complex physics with graph networks","author":"sanchez-gonzalez","year":"0","journal-title":"International Conference on Machine Learning"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2008.2005605"},{"key":"ref8","first-page":"490","article-title":"Learning to manipulate object collections using grounded state representations","volume":"100","author":"wilson","year":"0","journal-title":"Proceedings of the Conference on Robot Learning ser Proceedings of Machine Learning Research"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2019.8851984"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00299"},{"key":"ref9","article-title":"Same object, different grasps: Data and semantic knowledge for task-oriented grasping","author":"murali","year":"0","journal-title":"Conference on Robot Learning"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TOH.2014.2326867"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2019.8794435"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA40945.2020.9197413"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2018.2810544"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48506.2021.9561473"},{"key":"ref23","first-page":"652","article-title":"Pointnet: Deep learning on point sets for 3d classification and segmentation","author":"qi","year":"0","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"},{"key":"ref26","article-title":"Socialgcn: An efficient graph convolutional network based model for social recommendation","author":"wu","year":"2018","journal-title":"ArXiv Preprint"},{"key":"ref25","article-title":"How powerful are graph neural networks?","author":"xu","year":"2018","journal-title":"ArXiv Preprint"}],"event":{"name":"2022 IEEE International Conference on Robotics and Automation (ICRA)","start":{"date-parts":[[2022,5,23]]},"location":"Philadelphia, PA, USA","end":{"date-parts":[[2022,5,27]]}},"container-title":["2022 International Conference on Robotics and Automation (ICRA)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9811522\/9811357\/09811601.pdf?arnumber=9811601","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,3]],"date-time":"2022-11-03T23:05:58Z","timestamp":1667516758000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9811601\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,23]]},"references-count":38,"URL":"https:\/\/doi.org\/10.1109\/icra46639.2022.9811601","relation":{},"subject":[],"published":{"date-parts":[[2022,5,23]]}}}