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Yaroslav Ganin and Victor Lempitsky. 2015. Unsupervised domain adaptation by backpropagation. In International conference on machine learning. PMLR, 1180\u20131189."},{"key":"e_1_3_2_1_13_1","volume-title":"Domain-adversarial training of neural networks. The journal of machine learning research 17, 1","author":"Ganin Yaroslav","year":"2016","unstructured":"Yaroslav Ganin , Evgeniya Ustinova , Hana Ajakan , Pascal Germain , Hugo Larochelle , Fran\u00e7ois Laviolette , Mario Marchand , and Victor Lempitsky . 2016. Domain-adversarial training of neural networks. The journal of machine learning research 17, 1 ( 2016 ), 2096\u20132030. Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan, Pascal Germain, Hugo Larochelle, Fran\u00e7ois Laviolette, Mario Marchand, and Victor Lempitsky. 2016. Domain-adversarial training of neural networks. 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In Proceedings of the IEEE\/CVF International Conference on Computer Vision. 3303\u20133312."},{"key":"e_1_3_2_1_16_1","volume-title":"Proceedings of the IEEE international conference on computer vision. 1521\u20131529","author":"Kehl Wadim","year":"2017","unstructured":"Wadim Kehl , Fabian Manhardt , Federico Tombari , Slobodan Ilic , and Nassir Navab . 2017 . Ssd-6d: Making rgb-based 3d detection and 6d pose estimation great again . In Proceedings of the IEEE international conference on computer vision. 1521\u20131529 . Wadim Kehl, Fabian Manhardt, Federico Tombari, Slobodan Ilic, and Nassir Navab. 2017. Ssd-6d: Making rgb-based 3d detection and 6d pose estimation great again. In Proceedings of the IEEE international conference on computer vision. 1521\u20131529."},{"key":"e_1_3_2_1_17_1","volume-title":"Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980","author":"Kingma P","year":"2014","unstructured":"Diederik\u00a0 P Kingma and Jimmy Ba . 2014 . 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Fabian Manhardt, Gu Wang, Benjamin Busam, Manuel Nickel, Sven Meier, Luca Minciullo, Xiangyang Ji, and Nassir Navab. 2020. CPS++: Improving class-level 6D pose and shape estimation from monocular images with self-supervised learning. arXiv preprint arXiv:2003.05848 (2020)."},{"key":"e_1_3_2_1_24_1","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 12435\u201312445","author":"Melas-Kyriazi Luke","year":"2021","unstructured":"Luke Melas-Kyriazi and Arjun\u00a0 K Manrai . 2021 . Pixmatch: Unsupervised domain adaptation via pixelwise consistency training . In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 12435\u201312445 . Luke Melas-Kyriazi and Arjun\u00a0K Manrai. 2021. Pixmatch: Unsupervised domain adaptation via pixelwise consistency training. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 12435\u201312445."},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_25_1","DOI":"10.1109\/CVPR42600.2020.00013"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_26_1","DOI":"10.1109\/CVPR42600.2020.01269"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_27_1","DOI":"10.1109\/CVPR.2019.00025"},{"key":"e_1_3_2_1_28_1","volume-title":"Proceedings of the AAAI conference on artificial intelligence, Vol.\u00a032","author":"Pei Zhongyi","year":"2018","unstructured":"Zhongyi Pei , Zhangjie Cao , Mingsheng Long , and Jianmin Wang . 2018 . Multi-adversarial domain adaptation . In Proceedings of the AAAI conference on artificial intelligence, Vol.\u00a032 . Zhongyi Pei, Zhangjie Cao, Mingsheng Long, and Jianmin Wang. 2018. Multi-adversarial domain adaptation. In Proceedings of the AAAI conference on artificial intelligence, Vol.\u00a032."},{"key":"e_1_3_2_1_29_1","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence, Vol.\u00a036","author":"Peng Wanli","year":"2022","unstructured":"Wanli Peng , Jianhang Yan , Hongtao Wen , and Yi Sun . 2022 . Self-supervised category-level 6D object pose estimation with deep implicit shape representation . In Proceedings of the AAAI Conference on Artificial Intelligence, Vol.\u00a036 . 2082\u20132090. Wanli Peng, Jianhang Yan, Hongtao Wen, and Yi Sun. 2022. Self-supervised category-level 6D object pose estimation with deep implicit shape representation. In Proceedings of the AAAI Conference on Artificial Intelligence, Vol.\u00a036. 2082\u20132090."},{"key":"e_1_3_2_1_30_1","volume-title":"Fixmatch: Simplifying semi-supervised learning with consistency and confidence. 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Martin Sundermeyer, Zoltan-Csaba Marton, Maximilian Durner, Manuel Brucker, and Rudolph Triebel. 2018. Implicit 3d orientation learning for 6d object detection from rgb images. In Proceedings of the european conference on computer vision (ECCV). 699\u2013715."},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_34_1","DOI":"10.1109\/TCSVT.2019.2950449"},{"key":"e_1_3_2_1_35_1","volume-title":"Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results. Advances in neural information processing systems 30","author":"Tarvainen Antti","year":"2017","unstructured":"Antti Tarvainen and Harri Valpola . 2017. Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results. Advances in neural information processing systems 30 ( 2017 ). Antti Tarvainen and Harri Valpola. 2017. Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results. Advances in neural information processing systems 30 (2017)."},{"key":"e_1_3_2_1_36_1","volume-title":"Proceedings, Part XXI 16","author":"Tian Meng","year":"2020","unstructured":"Meng Tian , Marcelo\u00a0 H Ang , and Gim\u00a0Hee Lee . 2020 . Shape prior deformation for categorical 6d object pose and size estimation. In Computer Vision\u2013ECCV 2020: 16th European Conference, Glasgow, UK, August 23\u201328, 2020 , Proceedings, Part XXI 16 . Springer, 530\u2013546. Meng Tian, Marcelo\u00a0H Ang, and Gim\u00a0Hee Lee. 2020. Shape prior deformation for categorical 6d object pose and size estimation. In Computer Vision\u2013ECCV 2020: 16th European Conference, Glasgow, UK, August 23\u201328, 2020, Proceedings, Part XXI 16. 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Self-labeled techniques for semi-supervised learning: taxonomy, software and empirical study. Knowledge and Information systems 42 ( 2015 ), 245\u2013284. Isaac Triguero, Salvador Garc\u00eda, and Francisco Herrera. 2015. Self-labeled techniques for semi-supervised learning: taxonomy, software and empirical study. Knowledge and Information systems 42 (2015), 245\u2013284."},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_39_1","DOI":"10.1109\/CVPR.2017.316"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_40_1","DOI":"10.1109\/34.88573"},{"key":"e_1_3_2_1_41_1","volume-title":"Attention is all you need. Advances in neural information processing systems 30","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani , Noam Shazeer , Niki Parmar , Jakob Uszkoreit , Llion Jones , Aidan\u00a0 N Gomez , \u0141ukasz Kaiser , and Illia Polosukhin . 2017. Attention is all you need. Advances in neural information processing systems 30 ( 2017 ). Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan\u00a0N Gomez, \u0141ukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. Advances in neural information processing systems 30 (2017)."},{"key":"e_1_3_2_1_42_1","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 2642\u20132651","author":"Wang He","year":"2019","unstructured":"He Wang , Srinath Sridhar , Jingwei Huang , Julien Valentin , Shuran Song , and Leonidas\u00a0 J Guibas . 2019 . Normalized object coordinate space for category-level 6d object pose and size estimation . In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 2642\u20132651 . He Wang, Srinath Sridhar, Jingwei Huang, Julien Valentin, Shuran Song, and Leonidas\u00a0J Guibas. 2019. Normalized object coordinate space for category-level 6d object pose and size estimation. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 2642\u20132651."},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"crossref","first-page":"2510","DOI":"10.1109\/LRA.2023.3254463","article-title":"Self-Supervised Category-Level 6D Object Pose Estimation With Optical Flow Consistency","volume":"8","author":"Zaccaria Michela","year":"2023","unstructured":"Michela Zaccaria , Fabian Manhardt , Yan Di , Federico Tombari , Jacopo Aleotti , and Mikhail Giorgini . 2023 . Self-Supervised Category-Level 6D Object Pose Estimation With Optical Flow Consistency . IEEE Robotics and Automation Letters 8 , 5 (2023), 2510 \u2013 2517 . Michela Zaccaria, Fabian Manhardt, Yan Di, Federico Tombari, Jacopo Aleotti, and Mikhail Giorgini. 2023. Self-Supervised Category-Level 6D Object Pose Estimation With Optical Flow Consistency. IEEE Robotics and Automation Letters 8, 5 (2023), 2510\u20132517.","journal-title":"IEEE Robotics and Automation Letters"},{"key":"e_1_3_2_1_44_1","first-page":"27469","article-title":"Category-level 6d object pose estimation in the wild: A semi-supervised learning approach and a new dataset","volume":"35","author":"Ze Yanjie","year":"2022","unstructured":"Yanjie Ze and Xiaolong Wang . 2022 . Category-level 6d object pose estimation in the wild: A semi-supervised learning approach and a new dataset . Advances in Neural Information Processing Systems 35 (2022), 27469 \u2013 27483 . Yanjie Ze and Xiaolong Wang. 2022. Category-level 6d object pose estimation in the wild: A semi-supervised learning approach and a new dataset. Advances in Neural Information Processing Systems 35 (2022), 27469\u201327483.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_45_1","volume-title":"2017 IEEE international conference on robotics and automation (ICRA). IEEE, 1386\u20131383","author":"Zeng Andy","year":"2017","unstructured":"Andy Zeng , Kuan-Ting Yu , Shuran Song , Daniel Suo , Ed Walker , Alberto Rodriguez , and Jianxiong Xiao . 2017 . Multi-view self-supervised deep learning for 6d pose estimation in the amazon picking challenge . In 2017 IEEE international conference on robotics and automation (ICRA). IEEE, 1386\u20131383 . Andy Zeng, Kuan-Ting Yu, Shuran Song, Daniel Suo, Ed Walker, Alberto Rodriguez, and Jianxiong Xiao. 2017. Multi-view self-supervised deep learning for 6d pose estimation in the amazon picking challenge. In 2017 IEEE international conference on robotics and automation (ICRA). IEEE, 1386\u20131383."},{"key":"e_1_3_2_1_46_1","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 8833\u20138842","author":"Zhang Cheng","year":"2021","unstructured":"Cheng Zhang , Zhaopeng Cui , Yinda Zhang , Bing Zeng , Marc Pollefeys , and Shuaicheng Liu . 2021 . Holistic 3d scene understanding from a single image with implicit representation . In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 8833\u20138842 . Cheng Zhang, Zhaopeng Cui, Yinda Zhang, Bing Zeng, Marc Pollefeys, and Shuaicheng Liu. 2021. Holistic 3d scene understanding from a single image with implicit representation. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 8833\u20138842."},{"key":"e_1_3_2_1_47_1","volume-title":"Context-aware mixup for domain adaptive semantic segmentation","author":"Zhou Qianyu","year":"2022","unstructured":"Qianyu Zhou , Zhengyang Feng , Qiqi Gu , Jiangmiao Pang , Guangliang Cheng , Xuequan Lu , Jianping Shi , and Lizhuang Ma. 2022. Context-aware mixup for domain adaptive semantic segmentation . IEEE Transactions on Circuits and Systems for Video Technology ( 2022 ). Qianyu Zhou, Zhengyang Feng, Qiqi Gu, Jiangmiao Pang, Guangliang Cheng, Xuequan Lu, Jianping Shi, and Lizhuang Ma. 2022. Context-aware mixup for domain adaptive semantic segmentation. 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