{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T15:56:17Z","timestamp":1778255777859,"version":"3.51.4"},"reference-count":28,"publisher":"SAGE Publications","issue":"12","license":[{"start":{"date-parts":[[2023,8,19]],"date-time":"2023-08-19T00:00:00Z","timestamp":1692403200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61772332"],"award-info":[{"award-number":["61772332"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["The International Journal of Robotics Research"],"published-print":{"date-parts":[[2023,10]]},"abstract":"<jats:p>Robust object grasping in cluttered scenes is vital to all robotic prehensile manipulation. In this paper, we present the GraspNet-1Billion benchmark that contains rich real-world captured cluttered scenarios and abundant annotations. This benchmark aims at solving two critical problems for the cluttered scenes parallel-finger grasping: the insufficient real-world training data and the lacking of evaluation benchmark. We first contribute a large-scale grasp pose detection dataset. Two different depth cameras based on structured-light and time-of-flight technologies are adopted. Our dataset contains 97,280 RGB-D images with over one billion grasp poses. In total, 190 cluttered scenes are collected, among which 100 are training set and 90 are for testing. Meanwhile, we build an evaluation system that is general and user-friendly. It directly reports a predicted grasp pose\u2019s quality by analytic computation, which is able to evaluate any kind of grasp representation without exhaustively labeling the ground-truth. We further divide the test set into three difficulties to better evaluate algorithms\u2019 generalization ability. Our dataset, accessing API and evaluation code, are publicly available at www.graspnet.net.<\/jats:p>","DOI":"10.1177\/02783649231193710","type":"journal-article","created":{"date-parts":[[2023,8,19]],"date-time":"2023-08-19T06:28:17Z","timestamp":1692426497000},"page":"1094-1103","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":26,"title":["Robust grasping across diverse sensor qualities: The GraspNet-1Billion dataset"],"prefix":"10.1177","volume":"42","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0758-0293","authenticated-orcid":false,"given":"Hao-Shu","family":"Fang","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Minghao","family":"Gou","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chenxi","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cewu","family":"Lu","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China"},{"name":"Shanghai AI Lab, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2023,8,19]]},"reference":[{"key":"bibr1-02783649231193710","doi-asserted-by":"publisher","DOI":"10.3390\/mti2030057"},{"key":"bibr2-02783649231193710","doi-asserted-by":"publisher","DOI":"10.1177\/0278364917700714"},{"key":"bibr3-02783649231193710","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2018.2852777"},{"key":"bibr4-02783649231193710","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2018.8593950"},{"key":"bibr5-02783649231193710","doi-asserted-by":"publisher","DOI":"10.1007\/s40747-021-00459-x"},{"key":"bibr6-02783649231193710","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-020-09888-5"},{"key":"bibr7-02783649231193710","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48506.2021.9560844"},{"key":"bibr8-02783649231193710","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01146"},{"key":"bibr9-02783649231193710","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2014.01.005"},{"key":"bibr10-02783649231193710","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48506.2021.9561409"},{"key":"bibr11-02783649231193710","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-33885-4_60"},{"key":"bibr12-02783649231193710","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2011.5980145"},{"key":"bibr13-02783649231193710","doi-asserted-by":"publisher","DOI":"10.3390\/s22166208"},{"key":"bibr14-02783649231193710","doi-asserted-by":"publisher","DOI":"10.1177\/0278364917710318"},{"key":"bibr15-02783649231193710","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10602-1_48"},{"key":"bibr16-02783649231193710","doi-asserted-by":"crossref","unstructured":"Mahler J, Liang J, Niyaz S, et al. (2017) Dex-Net 2.0: deep learning to plan robust grasps with synthetic point clouds and analytic grasp metrics. Proceedings of the Robotics: Science and Systems, Massachusetts, USA, July 12-16, 2017, The MIT press.","DOI":"10.15607\/RSS.2017.XIII.058"},{"key":"bibr17-02783649231193710","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2020.2992195"},{"key":"bibr18-02783649231193710","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00299"},{"key":"bibr19-02783649231193710","doi-asserted-by":"publisher","DOI":"10.1109\/TRO.2023.3280597."},{"key":"bibr20-02783649231193710","doi-asserted-by":"publisher","DOI":"10.1177\/027836498800700301"},{"key":"bibr21-02783649231193710","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2016.7487517"},{"key":"bibr22-02783649231193710","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2015.7139361"},{"key":"bibr23-02783649231193710","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00708"},{"key":"bibr24-02783649231193710","unstructured":"Sintov A, Ben-David I (2022) \u2018Simple kinesthetic haptics for object recognition\u2019,\n                      arXiv preprint arXiv:2206.05601\n                      ."},{"key":"bibr325-02783649231193710","doi-asserted-by":"publisher","DOI":"10.1177\/0278364917735594"},{"key":"bibr25-02783649231193710","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01566"},{"key":"bibr27-02783649231193710","doi-asserted-by":"publisher","DOI":"10.1109\/IROS40897.2019.8967869"},{"key":"bibr28-02783649231193710","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2022.3142401"}],"container-title":["The International Journal of Robotics Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/02783649231193710","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/02783649231193710","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/02783649231193710","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T10:17:01Z","timestamp":1777457821000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/02783649231193710"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8,19]]},"references-count":28,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2023,10]]}},"alternative-id":["10.1177\/02783649231193710"],"URL":"https:\/\/doi.org\/10.1177\/02783649231193710","relation":{},"ISSN":["0278-3649","1741-3176"],"issn-type":[{"value":"0278-3649","type":"print"},{"value":"1741-3176","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,8,19]]}}}