{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T13:19:19Z","timestamp":1753881559856,"version":"3.41.2"},"reference-count":40,"publisher":"World Scientific Pub Co Pte Ltd","issue":"02","funder":[{"DOI":"10.13039\/501100001809","name":"NSFC","doi-asserted-by":"crossref","award":["62176027"],"award-info":[{"award-number":["62176027"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["T2222018"],"award-info":[{"award-number":["T2222018"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100005230","name":"Chongqing Natural Science Foundation","doi-asserted-by":"crossref","award":["cstc2019jcyj-cxttX0003"],"award-info":[{"award-number":["cstc2019jcyj-cxttX0003"]}],"id":[{"id":"10.13039\/501100005230","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Patt. Recogn. Artif. Intell."],"published-print":{"date-parts":[[2025,2]]},"abstract":"<jats:p> In this paper, we introduce a novel system to assist 6D object pose estimation network training, which is only deployed in the training progress to optimize the network parameters, and does not work in the testing stage, called Online training and offline testing system (OTOT). OTOT consists of two modules: a feature fusion module and a supervision module. The feature fusion module fuses several feature maps from the pose estimation network in a specified order to obtain a fused feature. Then, the supervision module uses the encoder\u2013decoder structure network to implicitly extract useful features from the fused feature and optimizes the pose estimation network online through the back-propagation mechanism. OTOT can be migrated to any network with encoder\u2013decoder structure. The network trained with OTOT achieves 56.11% accuracy in terms of the VSD metric on the TLESS dataset using RGB inputs, compared to the 46.70% accuracy of the original network trained without OTOT. Experiments show that OTOT greatly improves the accuracy of the pose estimation network, and since OTOT is not deployed in the testing stage, it does not increase any parameters during testing and affect the original speed of the network. <\/jats:p>","DOI":"10.1142\/s0218001423510151","type":"journal-article","created":{"date-parts":[[2023,8,18]],"date-time":"2023-08-18T01:42:01Z","timestamp":1692322921000},"source":"Crossref","is-referenced-by-count":0,"title":["OTOT: An Online Training and Offline Testing System for 6D Object Pose Estimation"],"prefix":"10.1142","volume":"39","author":[{"given":"Yilin","family":"Yuan","sequence":"first","affiliation":[{"name":"State Key Laboratory of Mechanical Transmissions, School of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400000, P.\u00a0R.\u00a0China"}]},{"given":"Qian","family":"Jiang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Mechanical Transmissions, School of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400000, P.\u00a0R.\u00a0China"}]},{"given":"Quan","family":"Mu","sequence":"additional","affiliation":[{"name":"Ministry of Ecology and Environment, Foreign Environmental Cooperation Center, Beijing 100035, P.\u00a0R.\u00a0China"}]},{"given":"Wenchao","family":"Jia","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Mechanical Transmissions, School of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400000, P.\u00a0R.\u00a0China"}]},{"given":"Boya","family":"Fu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Mechanical Transmissions, School of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400000, P.\u00a0R.\u00a0China"}]},{"given":"Renzhi","family":"He","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Mechanical Transmissions, School of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400000, P.\u00a0R.\u00a0China"}]},{"given":"Jian","family":"Wen","sequence":"additional","affiliation":[{"name":"Powerchina Sichuan Electric Power Engineering Co., Ltd, Chengdu, Sichuan 610041, P.\u00a0R.\u00a0China"}]},{"given":"Fei","family":"Liu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Mechanical Transmissions, School of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400000, P.\u00a0R.\u00a0China"}]},{"given":"Qin","family":"Mao","sequence":"additional","affiliation":[{"name":"School of Computer and Information Technology, Qiannan Normal University for Nationalities, Duyun 558000, P.\u00a0R.\u00a0China"},{"name":"Key Laboratory of Complex Systems and Intelligent Optimization of Guizhou Province, Duyun 558000, P.\u00a0R.\u00a0China"}]},{"given":"Mingliang","family":"Zhou","sequence":"additional","affiliation":[{"name":"College of Computer Science, Chongqing University, Chongqing 400000, P.\u00a0R.\u00a0China"}]}],"member":"219","published-online":{"date-parts":[[2025,3,21]]},"reference":[{"key":"S0218001423510151BIB001","doi-asserted-by":"publisher","DOI":"10.1109\/WACV45572.2020.9093450"},{"key":"S0218001423510151BIB002","doi-asserted-by":"publisher","DOI":"10.1007\/11744023_32"},{"key":"S0218001423510151BIB004","doi-asserted-by":"publisher","DOI":"10.1109\/WACV45572.2020.9093272"},{"key":"S0218001423510151BIB005","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00429"},{"key":"S0218001423510151BIB006","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2019.XV.049"},{"key":"S0218001423510151BIB007","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01217"},{"key":"S0218001423510151BIB008","doi-asserted-by":"publisher","DOI":"10.1145\/358669.358692"},{"key":"S0218001423510151BIB009","volume-title":"2018 Advances in Neural Information Processing Systems (NIPS)","volume":"31","author":"Ghiasi G.","year":"2018"},{"key":"S0218001423510151BIB010","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00302"},{"key":"S0218001423510151BIB011","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01165"},{"key":"S0218001423510151BIB012","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"S0218001423510151BIB013","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-33885-4_60"},{"key":"S0218001423510151BIB014","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01172"},{"key":"S0218001423510151BIB015","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2017.103"},{"key":"S0218001423510151BIB016","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00300"},{"key":"S0218001423510151BIB017","first-page":"606","volume-title":"14th European Conf. 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