{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T01:28:45Z","timestamp":1770341325303,"version":"3.49.0"},"reference-count":64,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2023,8,25]],"date-time":"2023-08-25T00:00:00Z","timestamp":1692921600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key R&D Program of China","doi-asserted-by":"crossref","award":["2020YFC1522900"],"award-info":[{"award-number":["2020YFC1522900"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100021171","name":"Guangdong Basic and Applied Basic Research Foundation","doi-asserted-by":"crossref","award":["2021A1515011913"],"award-info":[{"award-number":["2021A1515011913"]}],"id":[{"id":"10.13039\/501100021171","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Funds of South Central Minzu University","award":["CZT20001"],"award-info":[{"award-number":["CZT20001"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Multimedia Comput. Commun. Appl."],"published-print":{"date-parts":[[2024,1,31]]},"abstract":"<jats:p>Due to intra-modality variations and cross-modality discrepancy, visible-infrared person re-identification (VI Re-ID) is an important and challenging task in intelligent video surveillance. The cross-modality discrepancy is mainly caused by the differences between visible images and infrared images, the inherent essence of which is heterogeneous. To alleviate this discrepancy, we propose a Dynamic Weighted Gradient Reversal Network (DGRNet) to enhance the learning of discriminative common representations by confusing the modality discrimination. In the proposed DGRNet, we design the gradient reversal model guiding adversarial training between identity classifier and modality discriminator to reduce the modality discrepancy of the same person in different modalities. Furthermore, we propose an optimization training method, that is, designing dynamic weight of gradient reversal to achieve optimal adversarial training, and dynamic weight has the ability to dynamically and adaptively evaluate the significance of target loss term, without involving hyper-parameter tuning. Extensive experiments were conducted on two public VI Re-ID datasets, SYSU-MM01 and RegDB. The experimental results show that the proposed DGRNet outperforms state-of-the-art methods and demonstrate the effectiveness of the DGRNet to learn more discriminative common representations for VI Re-ID.<\/jats:p>","DOI":"10.1145\/3607535","type":"journal-article","created":{"date-parts":[[2023,7,7]],"date-time":"2023-07-07T11:55:19Z","timestamp":1688730919000},"page":"1-23","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Dynamic Weighted Gradient Reversal Network for Visible-infrared Person Re-identification"],"prefix":"10.1145","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6392-3342","authenticated-orcid":false,"given":"Chenghua","family":"Li","sequence":"first","affiliation":[{"name":"South Central Minzu University, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-4688-1002","authenticated-orcid":false,"given":"Zongze","family":"Li","sequence":"additional","affiliation":[{"name":"South Central Minzu University, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5783-8133","authenticated-orcid":false,"given":"Jing","family":"Sun","sequence":"additional","affiliation":[{"name":"Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9457-7801","authenticated-orcid":false,"given":"Yun","family":"Zhang","sequence":"additional","affiliation":[{"name":"Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8712-1002","authenticated-orcid":false,"given":"Xiaoping","family":"Jiang","sequence":"additional","affiliation":[{"name":"South Central Minzu University, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-5469-2440","authenticated-orcid":false,"given":"Fan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Shenzhen Beidou Applied Technology Research Institute, China"}]}],"member":"320","published-online":{"date-parts":[[2023,8,25]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2019.107036"},{"key":"e_1_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-009-5152-4"},{"key":"e_1_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2022.3141868"},{"key":"e_1_3_1_5_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00065"},{"key":"e_1_3_1_6_2","doi-asserted-by":"publisher","DOI":"10.1109\/ISCAS51556.2021.9401292"},{"key":"e_1_3_1_7_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01027"},{"key":"e_1_3_1_8_2","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/94"},{"key":"e_1_3_1_9_2","doi-asserted-by":"publisher","DOI":"10.1145\/3243316"},{"key":"e_1_3_1_10_2","first-page":"1180","volume-title":"International Conference on Machine Learning","author":"Ganin Yaroslav","year":"2015","unstructured":"Yaroslav Ganin and Victor Lempitsky. 2015. Unsupervised domain adaptation by backpropagation. In International Conference on Machine Learning. PMLR, 1180\u20131189."},{"key":"e_1_3_1_11_2","first-page":"1","article-title":"Leaning compact and representative features for cross-modality person re-identification","author":"Gao Guangwei","year":"2022","unstructured":"Guangwei Gao, Hao Shao, Fei Wu, Meng Yang, and Yi Yu. 2022. Leaning compact and representative features for cross-modality person re-identification. WWW J. (2022), 1\u201318.","journal-title":"WWW J."},{"key":"e_1_3_1_12_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01609"},{"key":"e_1_3_1_13_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_3_1_14_2","article-title":"In defense of the triplet loss for person re-identification","author":"Hermans Alexander","year":"2017","unstructured":"Alexander Hermans, Lucas Beyer, and Bastian Leibe. 2017. In defense of the triplet loss for person re-identification. arXiv:1703.07737. Retrieved from https:\/\/arxiv.org\/abs\/1703.07737.","journal-title":"arXiv:1703.07737"},{"key":"e_1_3_1_15_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2020.2980201"},{"key":"e_1_3_1_16_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2020.3005314"},{"key":"e_1_3_1_17_2","article-title":"Exploring modality-shared appearance features and modality-invariant relation features for cross-modality person re-identification","author":"Huang Nianchang","year":"2021","unstructured":"Nianchang Huang, Jianan Liu, Qiang Zhang, and Jungong Han. 2021. Exploring modality-shared appearance features and modality-invariant relation features for cross-modality person re-identification. arXiv:2104.11539. Retrieved from https:\/\/arxiv.org\/abs\/2104.11539.","journal-title":"arXiv:2104.11539"},{"key":"e_1_3_1_18_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2019.2963721"},{"key":"e_1_3_1_19_2","first-page":"0","volume-title":"Proceedings of the European Conference on Computer Vision (ECCV\u201918) Workshops","author":"Kniaz Vladimir V.","year":"2018","unstructured":"Vladimir V. Kniaz, Vladimir A. Knyaz, Jiri Hladuvka, Walter G. Kropatsch, and Vladimir Mizginov. 2018. Thermalgan: Multimodal color-to-thermal image translation for person re-identification in multispectral dataset. In Proceedings of the European Conference on Computer Vision (ECCV\u201918) Workshops. 0\u20130."},{"key":"e_1_3_1_20_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5891"},{"key":"e_1_3_1_21_2","doi-asserted-by":"publisher","DOI":"10.1145\/3412384"},{"key":"e_1_3_1_22_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2021.3092578"},{"key":"e_1_3_1_23_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.01.089"},{"key":"e_1_3_1_24_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2020.3042080"},{"key":"e_1_3_1_25_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2022.3168999"},{"key":"e_1_3_1_26_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01339"},{"key":"e_1_3_1_27_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2019.00190"},{"key":"e_1_3_1_28_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2020.2965491"},{"key":"e_1_3_1_29_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2019.2958756"},{"key":"e_1_3_1_30_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2021.3122072"},{"key":"e_1_3_1_31_2","doi-asserted-by":"publisher","DOI":"10.1068\/p2896"},{"key":"e_1_3_1_32_2","doi-asserted-by":"publisher","DOI":"10.3390\/s17030605"},{"key":"e_1_3_1_33_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2019.2938523"},{"key":"e_1_3_1_34_2","article-title":"Deep domain confusion: Maximizing for domain invariance","author":"Tzeng Eric","year":"2014","unstructured":"Eric Tzeng, Judy Hoffman, Ning Zhang, Kate Saenko, and Trevor Darrell. 2014. Deep domain confusion: Maximizing for domain invariance. arXiv:1412.3474. Retrieved from https:\/\/arxiv.org\/abs\/1412.3474.","journal-title":"arXiv:1412.3474"},{"issue":"11","key":"e_1_3_1_35_2","article-title":"Visualizing data using t-SNE.","volume":"9","author":"Maaten Laurens Van der","year":"2008","unstructured":"Laurens Van der Maaten and Geoffrey Hinton. 2008. Visualizing data using t-SNE. J. Mach. Learn. Res. 9, 11 (2008).","journal-title":"J. Mach. Learn. Res."},{"key":"e_1_3_1_36_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00372"},{"key":"e_1_3_1_37_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i07.6894"},{"key":"e_1_3_1_38_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2020.2999180"},{"key":"e_1_3_1_39_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00071"},{"key":"e_1_3_1_40_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00029"},{"key":"e_1_3_1_41_2","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3059713"},{"key":"e_1_3_1_42_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-019-01290-1"},{"key":"e_1_3_1_43_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.575"},{"key":"e_1_3_1_44_2","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2023.3244747"},{"key":"e_1_3_1_45_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00431"},{"key":"e_1_3_1_46_2","doi-asserted-by":"crossref","unstructured":"Bin Yang Jun Chen and Mang Ye. 2023. Top-K visual tokens transformer: Selecting tokens for visible-infrared person re-identification. Proceedings of the IEEE International Conference on Acoustics Speech and Signal Processing 1\u20135.","DOI":"10.1109\/ICASSP49357.2023.10097170"},{"key":"e_1_3_1_47_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2020.3045261"},{"key":"e_1_3_1_48_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2021.3139224"},{"key":"e_1_3_1_49_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.12293"},{"key":"e_1_3_1_50_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2019.2921454"},{"key":"e_1_3_1_51_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01331"},{"key":"e_1_3_1_52_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58520-4_14"},{"key":"e_1_3_1_53_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3054775"},{"key":"e_1_3_1_54_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2020.3001665"},{"key":"e_1_3_1_55_2","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/152"},{"key":"e_1_3_1_56_2","doi-asserted-by":"publisher","DOI":"10.1145\/3473341"},{"key":"e_1_3_1_57_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2019.2939564"},{"key":"e_1_3_1_58_2","doi-asserted-by":"crossref","unstructured":"Qiang Zhang Changzhou Lai Jianan Liu Nianchang Huang and Jungong Han. 2022. FMCNet: Feature-level modality compensation for visible-infrared person re-identification. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition 7339\u20137348.","DOI":"10.1109\/CVPR52688.2022.00720"},{"key":"e_1_3_1_59_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2021.3120881"},{"key":"e_1_3_1_60_2","article-title":"Hybrid modality metric learning for visible-infrared person re-identification","year":"2022","unstructured":"ZhangLa, GuoHaiyun, ZhuKuan, QiaoHonglin, HuangGaopan, ZhangSen, ZhangHuichen, SunJian, and WangJinqiao. 2022. Hybrid modality metric learning for visible-infrared person re-identification. ACM Trans. Multimedia Comput. Commun. Appl. (2022).","journal-title":"ACM Trans. Multimedia Comput. Commun. Appl."},{"key":"e_1_3_1_61_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i4.16466"},{"key":"e_1_3_1_62_2","doi-asserted-by":"publisher","DOI":"10.5555\/2919332.2919877"},{"key":"e_1_3_1_63_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2709749"},{"key":"e_1_3_1_64_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2021.3072171"},{"key":"e_1_3_1_65_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i07.7000"}],"container-title":["ACM Transactions on Multimedia Computing, Communications, and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3607535","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3607535","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T16:36:28Z","timestamp":1750178188000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3607535"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8,25]]},"references-count":64,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2024,1,31]]}},"alternative-id":["10.1145\/3607535"],"URL":"https:\/\/doi.org\/10.1145\/3607535","relation":{},"ISSN":["1551-6857","1551-6865"],"issn-type":[{"value":"1551-6857","type":"print"},{"value":"1551-6865","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,8,25]]},"assertion":[{"value":"2022-12-02","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-06-29","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-08-25","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}