{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T17:22:56Z","timestamp":1772644976021,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":62,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,10,26]],"date-time":"2023-10-26T00:00:00Z","timestamp":1698278400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,10,26]]},"DOI":"10.1145\/3581783.3612355","type":"proceedings-article","created":{"date-parts":[[2023,10,27]],"date-time":"2023-10-27T07:26:54Z","timestamp":1698391614000},"page":"4647-4656","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":12,"title":["Modality-agnostic Augmented Multi-Collaboration Representation for Semi-supervised Heterogenous Face Recognition"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6550-212X","authenticated-orcid":false,"given":"Decheng","family":"Liu","sequence":"first","affiliation":[{"name":"Xidian University, Xi'an, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-6891-3511","authenticated-orcid":false,"given":"Weizhao","family":"Yang","sequence":"additional","affiliation":[{"name":"Xidian University, Xi'an, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3448-2514","authenticated-orcid":false,"given":"Chunlei","family":"Peng","sequence":"additional","affiliation":[{"name":"Xidian University, Xi'an, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1435-489X","authenticated-orcid":false,"given":"Nannan","family":"Wang","sequence":"additional","affiliation":[{"name":"Xidian University, Xi'an, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0290-5757","authenticated-orcid":false,"given":"Ruimin","family":"Hu","sequence":"additional","affiliation":[{"name":"Xidian University, Xi'an, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1443-0776","authenticated-orcid":false,"given":"Xinbo","family":"Gao","sequence":"additional","affiliation":[{"name":"Chongqing University of Posts and Telecommunications, Chongqing, China"}]}],"member":"320","published-online":{"date-parts":[[2023,10,27]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/SMC.2013.210"},{"key":"e_1_3_2_1_2_1","volume-title":"Mixmatch: A holistic approach to semi-supervised learning. Advances in neural information processing systems 32","author":"Berthelot David","year":"2019","unstructured":"David Berthelot, Nicholas Carlini, Ian Goodfellow, Nicolas Papernot, Avital Oliver, and Colin A Raffel. 2019. Mixmatch: A holistic approach to semi-supervised learning. Advances in neural information processing systems 32 (2019)."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"crossref","unstructured":"Nicholas Carlini and David Wagner. 2017. Towards evaluating the robustness of neural networks. In 2017 ieee symposium on security and privacy (sp). Ieee 39--57.","DOI":"10.1109\/SP.2017.49"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW50498.2020.00359"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00525"},{"key":"e_1_3_2_1_6_1","volume-title":"Improved regularization of convolutional neural networks with cutout. arXiv preprint arXiv:1708.04552","author":"DeVries Terrance","year":"2017","unstructured":"Terrance DeVries and Graham W Taylor. 2017. Improved regularization of convolutional neural networks with cutout. arXiv preprint arXiv:1708.04552 (2017)."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/FG52635.2021.9666962"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/TBIOM.2021.3060641"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00795"},{"key":"e_1_3_2_1_10_1","volume-title":"Dual variational generation for low shot heterogeneous face recognition. Advances in neural information processing systems 32","author":"Fu Chaoyou","year":"2019","unstructured":"Chaoyou Fu, Xiang Wu, Yibo Hu, Huaibo Huang, and Ran He. 2019. Dual variational generation for low shot heterogeneous face recognition. Advances in neural information processing systems 32 (2019)."},{"key":"e_1_3_2_1_11_1","volume-title":"Dvg-face: Dual variational generation for heterogeneous face recognition","author":"Fu Chaoyou","year":"2021","unstructured":"Chaoyou Fu, Xiang Wu, Yibo Hu, Huaibo Huang, and Ran He. 2021. Dvg-face: Dual variational generation for heterogeneous face recognition. IEEE transactions on pattern analysis and machine intelligence 44, 6 (2021), 2938--2952."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3227180"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3422622"},{"key":"e_1_3_2_1_14_1","volume-title":"Semi-supervised learning by entropy minimization. Advances in neural information processing systems 17","author":"Grandvalet Yves","year":"2004","unstructured":"Yves Grandvalet and Yoshua Bengio. 2004. Semi-supervised learning by entropy minimization. Advances in neural information processing systems 17 (2004)."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_3_2_1_17_1","volume-title":"Semi-supervised domain generalizable person re-identification. arXiv preprint arXiv:2108.05045","author":"He Lingxiao","year":"2021","unstructured":"Lingxiao He, Wu Liu, Jian Liang, Kecheng Zheng, Xingyu Liao, Peng Cheng, and Tao Mei. 2021. Semi-supervised domain generalizable person re-identification. arXiv preprint arXiv:2108.05045 (2021)."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2020.107618"},{"key":"e_1_3_2_1_19_1","volume-title":"Wasserstein CNN: Learning invariant features for NIR-VIS face recognition","author":"He Ran","year":"2018","unstructured":"Ran He, Xiang Wu, Zhenan Sun, and Tieniu Tan. 2018. Wasserstein CNN: Learning invariant features for NIR-VIS face recognition. IEEE transactions on pattern analysis and machine intelligence 41, 7 (2018), 1761--1773."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2021.3105411"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.632"},{"key":"e_1_3_2_1_22_1","volume-title":"Multi-view discriminant analysis","author":"Kan Meina","year":"2015","unstructured":"Meina Kan, Shiguang Shan, Haihong Zhang, Shihong Lao, and Xilin Chen. 2015. Multi-view discriminant analysis. IEEE transactions on pattern analysis and machine intelligence 38, 1 (2015), 188--194."},{"key":"e_1_3_2_1_23_1","volume-title":"Workshop on challenges in representation learning, ICML","volume":"3","author":"Dong-Hyun","unstructured":"Dong-Hyun Lee et al. 2013. Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks. In Workshop on challenges in representation learning, ICML, Vol. 3. 896."},{"key":"e_1_3_2_1_24_1","volume-title":"Workshop on challenges in representation learning, ICML","volume":"3","author":"Dong-Hyun","unstructured":"Dong-Hyun Lee et al. 2013. Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks. In Workshop on challenges in representation learning, ICML, Vol. 3. 896."},{"key":"e_1_3_2_1_25_1","volume-title":"2012 IEEE Conference on Computer Vision and Pattern Recognition. IEEE, 2512--2517","author":"Lei Zhen","year":"2012","unstructured":"Zhen Lei, Dong Yi, and Stan Z Li. 2012. Discriminant image filter learning for face recognition with local binary pattern like representation. In 2012 IEEE Conference on Computer Vision and Pattern Recognition. IEEE, 2512--2517."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2021.3049955"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00413"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2013.59"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/2856058"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2019.2957285"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2020.107579"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.03.042"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2022.3177960"},{"key":"e_1_3_2_1_34_1","volume-title":"Towards deep learning models resistant to adversarial attacks. arXiv preprint arXiv:1706.06083","author":"Madry Aleksander","year":"2017","unstructured":"Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, and Adrian Vladu. 2017. Towards deep learning models resistant to adversarial attacks. arXiv preprint arXiv:1706.06083 (2017)."},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICB45273.2019.8987347"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5963"},{"key":"e_1_3_2_1_37_1","volume-title":"Aleksandra Kaszowska, Holly A Taylor, Arash Samani, et al.","author":"Panetta Karen","year":"2018","unstructured":"Karen Panetta, Qianwen Wan, Sos Agaian, Srijith Rajeev, Shreyas Kamath, Rahul Rajendran, Shishir Paramathma Rao, Aleksandra Kaszowska, Holly A Taylor, Arash Samani, et al. 2018. A comprehensive database for benchmarking imaging systems. IEEE transactions on pattern analysis and machine intelligence 42, 3 (2018), 509--520."},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1109\/FG52635.2021.9666943"},{"key":"e_1_3_2_1_39_1","volume-title":"Regularization with stochastic transformations and perturbations for deep semi-supervised learning. Advances in neural information processing systems 29","author":"Sajjadi Mehdi","year":"2016","unstructured":"Mehdi Sajjadi, Mehran Javanmardi, and Tolga Tasdizen. 2016. Regularization with stochastic transformations and perturbations for deep semi-supervised learning. Advances in neural information processing systems 29 (2016)."},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-49409-8_40"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.74"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-014-0696-6"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2011.5995350"},{"key":"e_1_3_2_1_44_1","volume-title":"Alexey Kurakin, and Chun-Liang Li.","author":"Sohn Kihyuk","year":"2020","unstructured":"Kihyuk Sohn, David Berthelot, Nicholas Carlini, Zizhao Zhang, Han Zhang, Colin A Raffel, Ekin Dogus Cubuk, Alexey Kurakin, and Chun-Liang Li. 2020. Fixmatch: Simplifying semi-supervised learning with consistency and confidence. Advances in neural information processing systems 33 (2020), 596--608."},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.12291"},{"key":"e_1_3_2_1_46_1","volume-title":"Self-Augmented Heterogeneous Face Recognition. In 2021 IEEE International Joint Conference on Biometrics (IJCB). IEEE, 1--8.","author":"Sun Zongcai","year":"2021","unstructured":"Zongcai Sun, Chaoyou Fu, Mandi Luo, and Ran He. 2021. Self-Augmented Heterogeneous Face Recognition. In 2021 IEEE International Joint Conference on Biometrics (IJCB). IEEE, 1--8."},{"key":"e_1_3_2_1_47_1","article-title":"Visualizing data using t-SNE","volume":"9","author":"der Maaten Laurens Van","year":"2008","unstructured":"Laurens Van der Maaten and Geoffrey Hinton. 2008. Visualizing data using t-SNE. Journal of machine learning research 9, 11 (2008).","journal-title":"Journal of machine learning research"},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-01793-3_33"},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2018.2833032"},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33019005"},{"key":"e_1_3_2_1_51_1","volume-title":"Unsupervised data augmentation for consistency training. Advances in neural information processing systems 33","author":"Xie Qizhe","year":"2020","unstructured":"Qizhe Xie, Zihang Dai, Eduard Hovy, Thang Luong, and Quoc Le. 2020. Unsupervised data augmentation for consistency training. Advances in neural information processing systems 33 (2020), 6256--6268."},{"key":"e_1_3_2_1_52_1","volume-title":"UK","author":"Xu Guodong","year":"2020","unstructured":"Guodong Xu, Ziwei Liu, Xiaoxiao Li, and Chen Change Loy. 2020. Knowledge distillation meets self-supervision. In Computer Vision-ECCV 2020: 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part IX. Springer, 588--604."},{"key":"e_1_3_2_1_53_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00358"},{"key":"e_1_3_2_1_54_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2022.3160595"},{"key":"e_1_3_2_1_55_1","volume-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision. 9348--9357","author":"Yin Bangjie","year":"2019","unstructured":"Bangjie Yin, Luan Tran, Haoxiang Li, Xiaohui Shen, and Xiaoming Liu. 2019. To- wards interpretable face recognition. In Proceedings of the IEEE\/CVF International Conference on Computer Vision. 9348--9357."},{"key":"e_1_3_2_1_56_1","doi-asserted-by":"publisher","DOI":"10.1109\/FG47880.2020.00004"},{"key":"e_1_3_2_1_57_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-021-01432-4"},{"key":"e_1_3_2_1_58_1","doi-asserted-by":"publisher","DOI":"10.1109\/BTAS.2017.8272687"},{"key":"e_1_3_2_1_59_1","volume-title":"International conference on machine learning. PMLR, 11278--11287","author":"Zhang Jingfeng","year":"2020","unstructured":"Jingfeng Zhang, Xilie Xu, Bo Han, Gang Niu, Lizhen Cui, Masashi Sugiyama, and Mohan Kankanhalli. 2020. Attacks which do not kill training make adversarial learning stronger. In International conference on machine learning. PMLR, 11278--11287."},{"key":"e_1_3_2_1_60_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00381"},{"key":"e_1_3_2_1_61_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00454"},{"key":"e_1_3_2_1_62_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00235"}],"event":{"name":"MM '23: The 31st ACM International Conference on Multimedia","location":"Ottawa ON Canada","acronym":"MM '23","sponsor":["SIGMM ACM Special Interest Group on Multimedia"]},"container-title":["Proceedings of the 31st ACM International Conference on Multimedia"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3581783.3612355","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3581783.3612355","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,21]],"date-time":"2025-08-21T23:59:41Z","timestamp":1755820781000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3581783.3612355"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,26]]},"references-count":62,"alternative-id":["10.1145\/3581783.3612355","10.1145\/3581783"],"URL":"https:\/\/doi.org\/10.1145\/3581783.3612355","relation":{},"subject":[],"published":{"date-parts":[[2023,10,26]]},"assertion":[{"value":"2023-10-27","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}