{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T11:38:25Z","timestamp":1781005105065,"version":"3.54.1"},"reference-count":88,"publisher":"Association for Computing Machinery (ACM)","issue":"2","license":[{"start":{"date-parts":[[2023,10,18]],"date-time":"2023-10-18T00:00:00Z","timestamp":1697587200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62076262, and 61673402, 61273270, and 60802069"],"award-info":[{"award-number":["62076262, and 61673402, 61273270, and 60802069"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"National Key Research and Development Program of China","award":["2018YFB1601101 and 2018YFB1601100"],"award-info":[{"award-number":["2018YFB1601101 and 2018YFB1601100"]}]},{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong Province","doi-asserted-by":"crossref","award":["2017A030311029"],"award-info":[{"award-number":["2017A030311029"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Multimedia Comput. Commun. Appl."],"published-print":{"date-parts":[[2024,2,29]]},"abstract":"<jats:p>Visible-Infrared Person Re-identification (VI-ReID) aims to search for the identity of the same person across different spectra. The feature maps obtained from the convolutional layers are generally used for loss calculation in the later stages of the model in VI-ReID, but their role in the early and middle stages of the model remains unexplored. In this article, we propose a novel Rethinking Convolutional Features (ReCF) approach for VI-ReID. ReCF consists of two modules: Middle Feature Generation (MFG), which utilizes the feature maps in the early stage to reduce significant modality gap, and Temporal Feature Aggregation (TFA), which uses the feature maps in the middle stage to aggregate multi-level features for enlarging the receptive field. MFG generates middle modality features in the form of a learnable convolution layer as a bridge between RGB and IR modalities, which is more flexible than using fixed-parameter grayscale images and yields a better middle modality to further reduce the modality gap. TFA first treats the convolution process as a video sequence, and the feature map of each convolution layer can be considered a worthwhile video frame. Based on this, we can obtain a multi-level receptive field and a temporal refinement. In addition, we introduce a color-unrelated loss and a modality-unrelated loss to constrain the modality features for providing a common feature representation space. Experimental results on the challenging VI-ReID datasets demonstrate that our proposed method achieves state-of-the-art performance.<\/jats:p>","DOI":"10.1145\/3617375","type":"journal-article","created":{"date-parts":[[2023,8,24]],"date-time":"2023-08-24T12:02:55Z","timestamp":1692878575000},"page":"1-20","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":8,"title":["A Feature Map is Worth a Video Frame: Rethinking Convolutional Features for Visible-Infrared Person Re-identification"],"prefix":"10.1145","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-2204-8668","authenticated-orcid":false,"given":"Qiaolin","family":"He","sequence":"first","affiliation":[{"name":"School of Electronics and Information Technology, Sun Yat-sen University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5584-1785","authenticated-orcid":false,"given":"Zhijie","family":"Zheng","sequence":"additional","affiliation":[{"name":"School of Electronics and Information Technology, Sun Yat-sen University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4884-323X","authenticated-orcid":false,"given":"Haifeng","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Electronics and Information Technology, Sun Yat-sen University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2023,10,18]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"crossref","first-page":"720","DOI":"10.1007\/978-3-031-25072-9_48","volume-title":"Proceedings of the Computer Vision\u2013ECCV 2022 Workshops: Tel Aviv","author":"Alehdaghi Mahdi","year":"2023","unstructured":"Mahdi Alehdaghi, Arthur Josi, Rafael MO Cruz, and Eric Granger. 2023. Visible-infrared person re-identification using privileged intermediate information. In Proceedings of the Computer Vision\u2013ECCV 2022 Workshops: Tel Aviv. Springer, 720\u2013737."},{"key":"e_1_3_1_3_2","first-page":"1806","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","author":"Branson Steve","year":"2013","unstructured":"Steve Branson, Oscar Beijbom, and Serge Belongie. 2013. Efficient large-scale structured learning. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 1806\u20131813."},{"key":"e_1_3_1_4_2","first-page":"1169","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","author":"Chen Dapeng","year":"2018","unstructured":"Dapeng Chen, Hongsheng Li, Tong Xiao, Shuai Yi, and Xiaogang Wang. 2018. Video person re-identification with competitive snippet-similarity aggregation and co-attentive snippet embedding. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 1169\u20131178."},{"key":"e_1_3_1_5_2","first-page":"2590","volume-title":"Proceedings of the IEEE International Conference on Computer Vision Workshops","author":"Chen Yanbei","year":"2017","unstructured":"Yanbei Chen, Xiatian Zhu, and Shaogang Gong. 2017. Person re-identification by deep learning multi-scale representations. In Proceedings of the IEEE International Conference on Computer Vision Workshops. 2590\u20132600."},{"key":"e_1_3_1_6_2","first-page":"1983","volume-title":"Proceedings of the IEEE International Conference on Computer Vision","author":"Chung Dahjung","year":"2017","unstructured":"Dahjung Chung, Khalid Tahboub, and Edward J. Delp. 2017. A two stream siamese convolutional neural network for person re-identification. In Proceedings of the IEEE International Conference on Computer Vision. 1983\u20131991."},{"key":"e_1_3_1_7_2","first-page":"6","volume-title":"Proceedings of the IJCAI","author":"Dai Pingyang","year":"2018","unstructured":"Pingyang Dai, Rongrong Ji, Haibin Wang, Qiong Wu, and Yuyu Huang. 2018. Cross-modality person re-identification with generative adversarial training. In Proceedings of the IJCAI. 6."},{"key":"e_1_3_1_8_2","doi-asserted-by":"crossref","first-page":"248","DOI":"10.1109\/CVPR.2009.5206848","volume-title":"Proceedings of the 2009 IEEE Conference on Computer Vision and Pattern Recognition","author":"Deng Jia","year":"2009","unstructured":"Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei. 2009. Imagenet: A large-scale hierarchical image database. In Proceedings of the 2009 IEEE Conference on Computer Vision and Pattern Recognition. IEEE, 248\u2013255."},{"key":"e_1_3_1_9_2","first-page":"8239","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","author":"Deng Zhongying","year":"2019","unstructured":"Zhongying Deng, Xiaojiang Peng, and Yu Qiao. 2019. Residual compensation networks for heterogeneous face recognition. In Proceedings of the AAAI Conference on Artificial Intelligence. 8239\u20138246."},{"key":"e_1_3_1_10_2","first-page":"12036","volume-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","author":"Eom Chanho","year":"2021","unstructured":"Chanho Eom, Geon Lee, Junghyup Lee, and Bumsub Ham. 2021. Video-based person re-identification with spatial and temporal memory networks. In Proceedings of the IEEE\/CVF International Conference on Computer Vision. 12036\u201312045."},{"key":"e_1_3_1_11_2","doi-asserted-by":"crossref","first-page":"579","DOI":"10.1109\/TIP.2019.2928126","article-title":"Learning modality-specific representations for visible-infrared person re-identification","volume":"29","author":"Feng Zhanxiang","year":"2019","unstructured":"Zhanxiang Feng, Jianhuang Lai, and Xiaohua Xie. 2019. Learning modality-specific representations for visible-infrared person re-identification. IEEE Transactions on Image Processing 29 (2019), 579\u2013590.","journal-title":"IEEE Transactions on Image Processing"},{"key":"e_1_3_1_12_2","unstructured":"Jiyang Gao and Ram Nevatia. 2018. Revisiting temporal modeling for video-based person reid. arXiv:1805.02104."},{"key":"e_1_3_1_13_2","first-page":"315","volume-title":"Proceedings of the 14th International Conference on Artificial Intelligence and Statistics","author":"Glorot Xavier","year":"2011","unstructured":"Xavier Glorot, Antoine Bordes, and Yoshua Bengio. 2011. Deep sparse rectifier neural networks. In Proceedings of the 14th International Conference on Artificial Intelligence and Statistics. JMLR Workshop and Conference Proceedings, 315\u2013323."},{"issue":"11","key":"e_1_3_1_14_2","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1145\/3422622","article-title":"Generative adversarial networks","volume":"63","author":"Goodfellow Ian","year":"2020","unstructured":"Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2020. Generative adversarial networks. Communications of the ACM 63, 11 (2020), 139\u2013144.","journal-title":"Communications of the ACM"},{"key":"e_1_3_1_15_2","first-page":"228","volume-title":"Proceedings of the European Conference on Computer Vision","author":"Gu Xinqian","year":"2020","unstructured":"Xinqian Gu, Hong Chang, Bingpeng Ma, Hongkai Zhang, and Xilin Chen. 2020. Appearance-preserving 3d convolution for video-based person re-identification. In Proceedings of the European Conference on Computer Vision. Springer, 228\u2013243."},{"key":"e_1_3_1_16_2","first-page":"8385","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","author":"Hao Yi","year":"2019","unstructured":"Yi Hao, Nannan Wang, Jie Li, and Xinbo Gao. 2019. HSME: Hypersphere manifold embedding for visible thermal person re-identification. In Proceedings of the AAAI Conference on Artificial Intelligence. 8385\u20138392."},{"key":"e_1_3_1_17_2","first-page":"770","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","author":"He Kaiming","year":"2016","unstructured":"Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016. Deep residual learning for image recognition. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 770\u2013778."},{"issue":"8","key":"e_1_3_1_18_2","doi-asserted-by":"crossref","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","article-title":"Long short-term memory","volume":"9","author":"Hochreiter Sepp","year":"1997","unstructured":"Sepp Hochreiter and J\u00fcrgen Schmidhuber. 1997. Long short-term memory. Neural Computation 9, 8 (1997), 1735\u20131780.","journal-title":"Neural Computation"},{"key":"e_1_3_1_19_2","first-page":"7132","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","author":"Hu Jie","year":"2018","unstructured":"Jie Hu, Li Shen, and Gang Sun. 2018. Squeeze-and-excitation networks. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 7132\u20137141."},{"key":"e_1_3_1_20_2","article-title":"Deep learning for visible-infrared cross-modality person re-identification: A comprehensive review","author":"Huang Nianchang","year":"2022","unstructured":"Nianchang Huang, Jianan Liu, Yunqi Miao, Qiang Zhang, and Jungong Han. 2022. Deep learning for visible-infrared cross-modality person re-identification: A comprehensive review. Information Fusion 91 (2022), 396\u2013411.","journal-title":"Information Fusion"},{"key":"e_1_3_1_21_2","first-page":"80","volume-title":"Proceedings of the CVPR Workshops","author":"Huang Peixiang","year":"2019","unstructured":"Peixiang Huang, Runhui Huang, Jianjie Huang, Rushi Yangchen, Zongyao He, Xiying Li, and Junzhou Chen. 2019. Deep feature fusion with multiple granularity for vehicle re-identification. In Proceedings of the CVPR Workshops. 80\u201388."},{"issue":"3","key":"e_1_3_1_22_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3565886","article-title":"Beyond the parts: Learning coarse-to-fine adaptive alignment representation for person search","volume":"19","author":"Huang Wenxin","year":"2023","unstructured":"Wenxin Huang, Xuemei Jia, Xian Zhong, Xiao Wang, Kui Jiang, and Zheng Wang. 2023. Beyond the parts: Learning coarse-to-fine adaptive alignment representation for person search. ACM Transactions on Multimedia Computing, Communications and Applications 19, 3 (2023), 1\u201319.","journal-title":"ACM Transactions on Multimedia Computing, Communications and Applications"},{"key":"e_1_3_1_23_2","doi-asserted-by":"crossref","first-page":"2671","DOI":"10.1109\/ICIP46576.2022.9897492","volume-title":"Proceedings of the 2022 IEEE International Conference on Image Processing (ICIP)","author":"Huang Ze","year":"2022","unstructured":"Ze Huang, Rui Huang, Li Sun, Cheng Zhao, Min Huang, and Songzhi Su. 2022. VEFNet: An event-RGB cross modality fusion network for visual place recognition. In Proceedings of the 2022 IEEE International Conference on Image Processing (ICIP). IEEE, 2671\u20132675."},{"key":"e_1_3_1_24_2","first-page":"448","volume-title":"Proceedings of the International Conference on Machine Learning","author":"Ioffe Sergey","year":"2015","unstructured":"Sergey Ioffe and Christian Szegedy. 2015. Batch normalization: Accelerating deep network training by reducing internal covariate shift. In Proceedings of the International Conference on Machine Learning. PMLR, 448\u2013456."},{"key":"e_1_3_1_25_2","first-page":"6399","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Kirillov Alexander","year":"2019","unstructured":"Alexander Kirillov, Ross Girshick, Kaiming He, and Piotr Doll\u00e1r. 2019. Panoptic feature pyramid networks. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 6399\u20136408."},{"key":"e_1_3_1_26_2","first-page":"0","volume-title":"Proceedings of the European Conference on Computer Vision (ECCV) 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) Workshops. 0\u20130."},{"key":"e_1_3_1_27_2","doi-asserted-by":"crossref","first-page":"2288","DOI":"10.1109\/CVPR.2012.6247939","volume-title":"Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition","author":"Koestinger Martin","year":"2012","unstructured":"Martin Koestinger, Martin Hirzer, Paul Wohlhart, Peter M. Roth, and Horst Bischof. 2012. Large scale metric learning from equivalence constraints. In Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition. IEEE, 2288\u20132295."},{"key":"e_1_3_1_28_2","first-page":"4610","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","author":"Li Diangang","year":"2020","unstructured":"Diangang Li, Xing Wei, Xiaopeng Hong, and Yihong Gong. 2020. Infrared-visible cross-modal person re-identification with an x modality. In Proceedings of the AAAI Conference on Artificial Intelligence. 4610\u20134617."},{"key":"e_1_3_1_29_2","doi-asserted-by":"crossref","first-page":"109315","DOI":"10.1016\/j.knosys.2022.109315","article-title":"Dual-stream reciprocal disentanglement learning for domain adaptation person re-identification","volume":"251","author":"Li Huafeng","year":"2022","unstructured":"Huafeng Li, Kaixiong Xu, Jinxing Li, and Zhengtao Yu. 2022. Dual-stream reciprocal disentanglement learning for domain adaptation person re-identification. Knowledge-Based Systems 251 (2022), 109315.","journal-title":"Knowledge-Based Systems"},{"key":"e_1_3_1_30_2","first-page":"8618","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","author":"Li Jianing","year":"2019","unstructured":"Jianing Li, Shiliang Zhang, and Tiejun Huang. 2019. Multi-scale 3d convolution network for video based person re-identification. In Proceedings of the AAAI Conference on Artificial Intelligence. 8618\u20138625."},{"key":"e_1_3_1_31_2","first-page":"737","volume-title":"Proceedings of the European Conference on Computer Vision (ECCV)","author":"Li Minxian","year":"2018","unstructured":"Minxian Li, Xiatian Zhu, and Shaogang Gong. 2018. Unsupervised person re-identification by deep learning tracklet association. In Proceedings of the European Conference on Computer Vision (ECCV). 737\u2013753."},{"key":"e_1_3_1_32_2","first-page":"2285","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","author":"Li Wei","year":"2018","unstructured":"Wei Li, Xiatian Zhu, and Shaogang Gong. 2018. Harmonious attention network for person re-identification. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2285\u20132294."},{"issue":"4","key":"e_1_3_1_33_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3412384","article-title":"Part-based structured representation learning for person re-identification","volume":"16","author":"Li Yaoyu","year":"2020","unstructured":"Yaoyu Li, Hantao Yao, Tianzhu Zhang, and Changsheng Xu. 2020. Part-based structured representation learning for person re-identification. ACM Transactions on Multimedia Computing, Communications, and Applications 16, 4 (2020), 1\u201322.","journal-title":"ACM Transactions on Multimedia Computing, Communications, and Applications"},{"key":"e_1_3_1_34_2","first-page":"8090","volume-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","author":"Li Yu-Jhe","year":"2019","unstructured":"Yu-Jhe Li, Yun-Chun Chen, Yen-Yu Lin, Xiaofei Du, and Yu-Chiang Frank Wang. 2019. Recover and identify: A generative dual model for cross-resolution person re-identification. In Proceedings of the IEEE\/CVF International Conference on Computer Vision. 8090\u20138099."},{"key":"e_1_3_1_35_2","first-page":"2197","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","author":"Liao Shengcai","year":"2015","unstructured":"Shengcai Liao, Yang Hu, Xiangyu Zhu, and Stan Z. Li. 2015. Person re-identification by local maximal occurrence representation and metric learning. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2197\u20132206."},{"key":"e_1_3_1_36_2","first-page":"20973","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Lin Xinyu","year":"2022","unstructured":"Xinyu Lin, Jinxing Li, Zeyu Ma, Huafeng Li, Shuang Li, Kaixiong Xu, Guangming Lu, and David Zhang. 2022. Learning modal-invariant and temporal-memory for video-based visible-infrared person re-identification. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 20973\u201320982."},{"key":"e_1_3_1_37_2","doi-asserted-by":"crossref","first-page":"889","DOI":"10.1145\/3394171.3413821","volume-title":"Proceedings of the 28th ACM International Conference on Multimedia","author":"Ling Yongguo","year":"2020","unstructured":"Yongguo Ling, Zhun Zhong, Zhiming Luo, Paolo Rota, Shaozi Li, and Nicu Sebe. 2020. Class-aware modality mix and center-guided metric learning for visible-thermal person re-identification. In Proceedings of the 28th ACM International Conference on Multimedia. 889\u2013897."},{"key":"e_1_3_1_38_2","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.neucom.2020.01.089","article-title":"Enhancing the discriminative feature learning for visible-thermal cross-modality person re-identification","volume":"398","author":"Liu Haijun","year":"2020","unstructured":"Haijun Liu, Jian Cheng, Wen Wang, Yanzhou Su, and Haiwei Bai. 2020. Enhancing the discriminative feature learning for visible-thermal cross-modality person re-identification. Neurocomputing 398 (2020), 11\u201319.","journal-title":"Neurocomputing"},{"issue":"1","key":"e_1_3_1_39_2","first-page":"1","article-title":"Dense 3D-convolutional neural network for person re-identification in videos","volume":"15","author":"Liu Jiawei","year":"2019","unstructured":"Jiawei Liu, Zheng-Jun Zha, Xuejin Chen, Zilei Wang, and Yongdong Zhang. 2019. Dense 3D-convolutional neural network for person re-identification in videos. ACM Transactions on Multimedia Computing, Communications, and Applications 15, 1s (2019), 1\u201319.","journal-title":"ACM Transactions on Multimedia Computing, Communications, and Applications"},{"key":"e_1_3_1_40_2","first-page":"8786","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","author":"Liu Yiheng","year":"2019","unstructured":"Yiheng Liu, Zhenxun Yuan, Wengang Zhou, and Houqiang Li. 2019. Spatial and temporal mutual promotion for video-based person re-identification. In Proceedings of the AAAI Conference on Artificial Intelligence. 8786\u20138793."},{"key":"e_1_3_1_41_2","doi-asserted-by":"crossref","first-page":"109741","DOI":"10.1016\/j.knosys.2022.109741","article-title":"Dual-stream cross-modality fusion transformer for RGB-D action recognition","volume":"255","author":"Liu Zhen","year":"2022","unstructured":"Zhen Liu, Jun Cheng, Libo Liu, Ziliang Ren, Qieshi Zhang, and Chengqun Song. 2022. Dual-stream cross-modality fusion transformer for RGB-D action recognition. Knowledge-Based Systems 255 (2022), 109741.","journal-title":"Knowledge-Based Systems"},{"key":"e_1_3_1_42_2","first-page":"3431","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","author":"Long Jonathan","year":"2015","unstructured":"Jonathan Long, Evan Shelhamer, and Trevor Darrell. 2015. Fully convolutional networks for semantic segmentation. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 3431\u20133440."},{"key":"e_1_3_1_43_2","first-page":"13379","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Lu Yan","year":"2020","unstructured":"Yan Lu, Yue Wu, Bin Liu, Tianzhu Zhang, Baopu Li, Qi Chu, and Nenghai Yu. 2020. Cross-modality person re-identification with shared-specific feature transfer. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 13379\u201313389."},{"issue":"10","key":"e_1_3_1_44_2","doi-asserted-by":"crossref","first-page":"2597","DOI":"10.1109\/TMM.2019.2958756","article-title":"A strong baseline and batch normalization neck for deep person re-identification","volume":"22","author":"Luo Hao","year":"2019","unstructured":"Hao Luo, Wei Jiang, Youzhi Gu, Fuxu Liu, Xingyu Liao, Shenqi Lai, and Jianyang Gu. 2019. A strong baseline and batch normalization neck for deep person re-identification. IEEE Transactions on Multimedia 22, 10 (2019), 2597\u20132609.","journal-title":"IEEE Transactions on Multimedia"},{"key":"e_1_3_1_45_2","first-page":"1325","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","author":"McLaughlin Niall","year":"2016","unstructured":"Niall McLaughlin, Jesus Martinez Del Rincon, and Paul Miller. 2016. Recurrent convolutional network for video-based person re-identification. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 1325\u20131334."},{"issue":"3","key":"e_1_3_1_46_2","doi-asserted-by":"crossref","first-page":"605","DOI":"10.3390\/s17030605","article-title":"Person recognition system based on a combination of body images from visible light and thermal cameras","volume":"17","author":"Nguyen Dat Tien","year":"2017","unstructured":"Dat Tien Nguyen, Hyung Gil Hong, Ki Wan Kim, and Kang Ryoung Park. 2017. Person recognition system based on a combination of body images from visible light and thermal cameras. Sensors 17, 3 (2017), 605.","journal-title":"Sensors"},{"key":"e_1_3_1_47_2","first-page":"12046","volume-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","author":"Park Hyunjong","year":"2021","unstructured":"Hyunjong Park, Sanghoon Lee, Junghyup Lee, and Bumsub Ham. 2021. Learning by aligning: Visible-infrared person re-identification using cross-modal correspondences. In Proceedings of the IEEE\/CVF International Conference on Computer Vision. 12046\u201312055."},{"issue":"1","key":"e_1_3_1_48_2","first-page":"1","article-title":"Greyreid: A novel two-stream deep framework with RGB-grey information for person re-identification","volume":"17","author":"Qi Lei","year":"2021","unstructured":"Lei Qi, Lei Wang, Jing Huo, Yinghuan Shi, and Yang Gao. 2021. Greyreid: A novel two-stream deep framework with RGB-grey information for person re-identification. ACM Transactions on Multimedia Computing, Communications, and Applications 17, 1 (2021), 1\u201322.","journal-title":"ACM Transactions on Multimedia Computing, Communications, and Applications"},{"key":"e_1_3_1_49_2","first-page":"5399","volume-title":"Proceedings of the IEEE International Conference on Computer Vision","author":"Qian Xuelin","year":"2017","unstructured":"Xuelin Qian, Yanwei Fu, Yu-Gang Jiang, Tao Xiang, and Xiangyang Xue. 2017. Multi-scale deep learning architectures for person re-identification. In Proceedings of the IEEE International Conference on Computer Vision. 5399\u20135408."},{"issue":"4","key":"e_1_3_1_50_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3402666","article-title":"Correlation discrepancy insight network for video re-identification","volume":"16","author":"Ruan Weijian","year":"2020","unstructured":"Weijian Ruan, Chao Liang, Yi Yu, Zheng Wang, Wu Liu, Jun Chen, and Jiayi Ma. 2020. Correlation discrepancy insight network for video re-identification. ACM Transactions on Multimedia Computing, Communications, and Applications 16, 4 (2020), 1\u201321.","journal-title":"ACM Transactions on Multimedia Computing, Communications, and Applications"},{"key":"e_1_3_1_51_2","first-page":"618","volume-title":"Proceedings of the IEEE International Conference on Computer Vision","author":"Selvaraju Ramprasaath R.","year":"2017","unstructured":"Ramprasaath R. Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Batra. 2017. Grad-cam: Visual explanations from deep networks via gradient-based localization. In Proceedings of the IEEE International Conference on Computer Vision. 618\u2013626."},{"issue":"2","key":"e_1_3_1_52_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3309881","article-title":"Multi-level similarity perception network for person re-identification","volume":"15","author":"Shen Chen","year":"2019","unstructured":"Chen Shen, Zhongming Jin, Wenqing Chu, Rongxin Jiang, Yaowu Chen, Guo-Jun Qi, and Xian-Sheng Hua. 2019. Multi-level similarity perception network for person re-identification. ACM Transactions on Multimedia Computing, Communications, and Applications 15, 2 (2019), 1\u201319.","journal-title":"ACM Transactions on Multimedia Computing, Communications, and Applications"},{"key":"e_1_3_1_53_2","first-page":"480","volume-title":"Proceedings of the European Conference on Computer Vision","author":"Sun Yifan","year":"2018","unstructured":"Yifan Sun, Liang Zheng, Yi Yang, Qi Tian, and Shengjin Wang. 2018. Beyond part models: Person retrieval with refined part pooling (and a strong convolutional baseline). In Proceedings of the European Conference on Computer Vision. 480\u2013496."},{"key":"e_1_3_1_54_2","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1145\/3240508.3240552","volume-title":"Proceedings of the 26th ACM International Conference on Multimedia","author":"Wang Guanshuo","year":"2018","unstructured":"Guanshuo Wang, Yufeng Yuan, Xiong Chen, Jiwei Li, and Xi Zhou. 2018. Learning discriminative features with multiple granularities for person re-identification. In Proceedings of the 26th ACM International Conference on Multimedia. 274\u2013282."},{"key":"e_1_3_1_55_2","first-page":"3623","volume-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","author":"Wang Guan\u2019an","year":"2019","unstructured":"Guan\u2019an Wang, Tianzhu Zhang, Jian Cheng, Si Liu, Yang Yang, and Zengguang Hou. 2019. RGB-infrared cross-modality person re-identification via joint pixel and feature alignment. In Proceedings of the IEEE\/CVF International Conference on Computer Vision. 3623\u20133632."},{"key":"e_1_3_1_56_2","first-page":"12144","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","author":"Wang Guan-An","year":"2020","unstructured":"Guan-An Wang, Tianzhu Zhang, Yang Yang, Jian Cheng, Jianlong Chang, Xu Liang, and Zeng-Guang Hou. 2020. Cross-modality paired-images generation for RGB-infrared person re-identification. In Proceedings of the AAAI Conference on Artificial Intelligence. 12144\u201312151."},{"key":"e_1_3_1_57_2","article-title":"Context sensing attention network for video-based person re-identification","author":"Wang Kan","year":"2022","unstructured":"Kan Wang, Changxing Ding, Jianxin Pang, and Xiangmin Xu. 2022. Context sensing attention network for video-based person re-identification. ACM Transactions on Multimedia Computing, Communications and Applications 19, 4 (2022), 1.20.","journal-title":"ACM Transactions on Multimedia Computing, Communications and Applications"},{"key":"e_1_3_1_58_2","first-page":"618","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Wang Zhixiang","year":"2019","unstructured":"Zhixiang Wang, Zheng Wang, Yinqiang Zheng, Yung-Yu Chuang, and Shin\u2019ichi Satoh. 2019. Learning to reduce dual-level discrepancy for infrared-visible person re-identification. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 618\u2013626."},{"issue":"6","key":"e_1_3_1_59_2","doi-asserted-by":"crossref","first-page":"1765","DOI":"10.1007\/s11263-019-01290-1","article-title":"Rgb-ir person re-identification by cross-modality similarity preservation","volume":"128","author":"Wu Ancong","year":"2020","unstructured":"Ancong Wu, Wei-Shi Zheng, Shaogang Gong, and Jianhuang Lai. 2020. Rgb-ir person re-identification by cross-modality similarity preservation. International Journal of Computer Vision 128, 6 (2020), 1765\u20131785.","journal-title":"International Journal of Computer Vision"},{"key":"e_1_3_1_60_2","first-page":"5380","volume-title":"Proceedings of the IEEE International Conference on Computer Vision","author":"Wu Ancong","year":"2017","unstructured":"Ancong Wu, Wei-Shi Zheng, Hong-Xing Yu, Shaogang Gong, and Jianhuang Lai. 2017. RGB-infrared cross-modality person re-identification. In Proceedings of the IEEE International Conference on Computer Vision. 5380\u20135389."},{"key":"e_1_3_1_61_2","first-page":"5177","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","author":"Wu Yu","year":"2018","unstructured":"Yu Wu, Yutian Lin, Xuanyi Dong, Yan Yan, Wanli Ouyang, and Yi Yang. 2018. Exploit the unknown gradually: One-shot video-based person re-identification by stepwise learning. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 5177\u20135186."},{"key":"e_1_3_1_62_2","volume-title":"Proceedings of the Asian Conference on Computer Vision","author":"Xiang Wangmeng","year":"2020","unstructured":"Wangmeng Xiang, Jianqiang Huang, Xian-Sheng Hua, and Lei Zhang. 2020. Part-aware attention network for person re-identification. In Proceedings of the Asian Conference on Computer Vision."},{"key":"e_1_3_1_63_2","doi-asserted-by":"crossref","first-page":"4250","DOI":"10.1109\/TMM.2022.3186177","article-title":"Sampling and re-weighting: Towards diverse frame aware unsupervised video person re-identification","volume":"24","author":"Xie Pengyu","year":"2022","unstructured":"Pengyu Xie, Xin Xu, Zheng Wang, and Toshihiko Yamasaki. 2022. Sampling and re-weighting: Towards diverse frame aware unsupervised video person re-identification. IEEE Transactions on Multimedia 24 (2022), 4250\u20134261.","journal-title":"IEEE Transactions on Multimedia"},{"key":"e_1_3_1_64_2","first-page":"4733","volume-title":"Proceedings of the IEEE International Conference on Computer Vision","author":"Xu Shuangjie","year":"2017","unstructured":"Shuangjie Xu, Yu Cheng, Kang Gu, Yang Yang, Shiyu Chang, and Pan Zhou. 2017. Jointly attentive spatial-temporal pooling networks for video-based person re-identification. In Proceedings of the IEEE International Conference on Computer Vision. 4733\u20134742."},{"key":"e_1_3_1_65_2","first-page":"3165","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","author":"Yair Noam","year":"2018","unstructured":"Noam Yair and Tomer Michaeli. 2018. Multi-scale weighted nuclear norm image restoration. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 3165\u20133174."},{"key":"e_1_3_1_66_2","first-page":"14308","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","author":"Yang Mouxing","year":"2022","unstructured":"Mouxing Yang, Zhenyu Huang, Peng Hu, Taihao Li, Jiancheng Lv, and Xi Peng. 2022. Learning with twin noisy labels for visible-infrared person re-identification. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 14308\u201314317."},{"key":"e_1_3_1_67_2","first-page":"536","volume-title":"Proceedings of the European Conference on Computer Vision","author":"Yang Yang","year":"2014","unstructured":"Yang Yang, Jimei Yang, Junjie Yan, Shengcai Liao, Dong Yi, and Stan Z Li. 2014. Salient color names for person re-identification. In Proceedings of the European Conference on Computer Vision. Springer, 536\u2013551."},{"issue":"6","key":"e_1_3_1_68_2","doi-asserted-by":"crossref","first-page":"2860","DOI":"10.1109\/TIP.2019.2891888","article-title":"Deep representation learning with part loss for person re-identification","volume":"28","author":"Yao Hantao","year":"2019","unstructured":"Hantao Yao, Shiliang Zhang, Richang Hong, Yongdong Zhang, Changsheng Xu, and Qi Tian. 2019. Deep representation learning with part loss for person re-identification. IEEE Transactions on Image Processing 28, 6 (2019), 2860\u20132871.","journal-title":"IEEE Transactions on Image Processing"},{"key":"e_1_3_1_69_2","first-page":"347","volume-title":"Proceedings of the 27th ACM International Conference on Multimedia","author":"Ye Mang","year":"2019","unstructured":"Mang Ye, Xiangyuan Lan, and Qingming Leng. 2019. Modality-aware collaborative learning for visible thermal person re-identification. In Proceedings of the 27th ACM International Conference on Multimedia. 347\u2013355."},{"key":"e_1_3_1_70_2","doi-asserted-by":"crossref","first-page":"9387","DOI":"10.1109\/TIP.2020.2998275","article-title":"Cross-modality person re-identification via modality-aware collaborative ensemble learning","volume":"29","author":"Ye Mang","year":"2020","unstructured":"Mang Ye, Xiangyuan Lan, Qingming Leng, and Jianbing Shen. 2020. Cross-modality person re-identification via modality-aware collaborative ensemble learning. IEEE Transactions on Image Processing 29 (2020), 9387\u20139399.","journal-title":"IEEE Transactions on Image Processing"},{"key":"e_1_3_1_71_2","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","author":"Ye Mang","year":"2018","unstructured":"Mang Ye, Xiangyuan Lan, Jiawei Li, and Pong Yuen. 2018. Hierarchical discriminative learning for visible thermal person re-identification. In Proceedings of the AAAI Conference on Artificial Intelligence."},{"key":"e_1_3_1_72_2","first-page":"407","article-title":"Bi-directional center-constrained top-ranking for visible thermal person re-identification","volume":"15","author":"Ye Mang","year":"2019","unstructured":"Mang Ye, Xiangyuan Lan, Zheng Wang, and Pong C. Yuen. 2019. Bi-directional center-constrained top-ranking for visible thermal person re-identification. IEEE Transactions on Information Forensics and Security 15 (2019), 407\u2013419.","journal-title":"IEEE Transactions on Information Forensics and Security"},{"key":"e_1_3_1_73_2","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","author":"Ye Mang","year":"2020","unstructured":"Mang Ye and Jianbing Shen. 2020. Probabilistic structural latent representation for unsupervised embedding. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)."},{"key":"e_1_3_1_74_2","first-page":"229","volume-title":"Proceedings of the European Conference on Computer Vision","author":"Ye Mang","year":"2020","unstructured":"Mang Ye, Jianbing Shen, David J. Crandall, Ling Shao, and Jiebo Luo. 2020. Dynamic dual-attentive aggregation learning for visible-infrared person re-identification. In Proceedings of the European Conference on Computer Vision. Springer, 229\u2013247."},{"issue":"6","key":"e_1_3_1_75_2","first-page":"2872","article-title":"Deep learning for person re-identification: A survey and outlook","volume":"44","author":"Ye Mang","year":"2021","unstructured":"Mang Ye, Jianbing Shen, Gaojie Lin, Tao Xiang, Ling Shao, and Steven C. H. Hoi. 2021. Deep learning for person re-identification: A survey and outlook. IEEE Transactions on Pattern Analysis and Machine Intelligence 44, 6 (2021), 2872\u20132893.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"e_1_3_1_76_2","first-page":"728","article-title":"Visible-infrared person re-identification via homogeneous augmented tri-modal learning","volume":"16","author":"Ye Mang","year":"2020","unstructured":"Mang Ye, Jianbing Shen, and Ling Shao. 2020. Visible-infrared person re-identification via homogeneous augmented tri-modal learning. IEEE Transactions on Information Forensics and Security 16 (2020), 728\u2013739.","journal-title":"IEEE Transactions on Information Forensics and Security"},{"key":"e_1_3_1_77_2","article-title":"Augmentation invariant and instance spreading feature for softmax embedding","author":"Ye Mang","year":"2020","unstructured":"Mang Ye, Jianbing Shen, Xu Zhang, Pong C. Yuen, and Shih-Fu Chang. 2020. Augmentation invariant and instance spreading feature for softmax embedding. IEEE Transactions on Pattern Analysis and Machine Intelligence 44, 2 (2020), 924\u2013939.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"e_1_3_1_78_2","first-page":"2","volume-title":"Proceedings of the IJCAI","author":"Ye Mang","year":"2018","unstructured":"Mang Ye, Zheng Wang, Xiangyuan Lan, and Pong C. Yuen. 2018. Visible thermal person re-identification via dual-constrained top-ranking. In Proceedings of the IJCAI. 2."},{"key":"e_1_3_1_79_2","article-title":"Searching parameterized retrieval and verification loss for re-identification","author":"Yuan Xin","year":"2023","unstructured":"Xin Yuan, Xin Xu, Zheng Wang, Kai Zhang, Wei Liu, and Ruimin Hu. 2023. Searching parameterized retrieval and verification loss for re-identification. IEEE Journal of Selected Topics in Signal Processing 17, 3 (2023), 560\u2013574.","journal-title":"IEEE Journal of Selected Topics in Signal Processing"},{"issue":"1","key":"e_1_3_1_80_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3473341","article-title":"Hybrid modality metric learning for visible-infrared person re-identification","volume":"18","author":"Zhang La","year":"2022","unstructured":"La Zhang, Haiyun Guo, Kuan Zhu, Honglin Qiao, Gaopan Huang, Sen Zhang, Huichen Zhang, Jian Sun, and Jinqiao Wang. 2022. Hybrid modality metric learning for visible-infrared person re-identification. ACM Transactions on Multimedia Computing, Communications, and Applications 18, 1s (2022), 1\u201315.","journal-title":"ACM Transactions on Multimedia Computing, Communications, and Applications"},{"key":"e_1_3_1_81_2","first-page":"7349","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Zhang Qiang","year":"2022","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. 7349\u20137358."},{"issue":"10","key":"e_1_3_1_82_2","doi-asserted-by":"crossref","first-page":"2768","DOI":"10.1109\/TCSVT.2017.2718188","article-title":"Learning bidirectional temporal cues for video-based person re-identification","volume":"28","author":"Zhang Wei","year":"2017","unstructured":"Wei Zhang, Xiaodong Yu, and Xuanyu He. 2017. Learning bidirectional temporal cues for video-based person re-identification. IEEE Transactions on Circuits and Systems for Video Technology 28, 10 (2017), 2768\u20132776.","journal-title":"IEEE Transactions on Circuits and Systems for Video Technology"},{"key":"e_1_3_1_83_2","first-page":"8514","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Zheng Feng","year":"2019","unstructured":"Feng Zheng, Cheng Deng, Xing Sun, Xinyang Jiang, Xiaowei Guo, Zongqiao Yu, Feiyue Huang, and Rongrong Ji. 2019. Pyramidal person re-identification via multi-loss dynamic training. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 8514\u20138522."},{"key":"e_1_3_1_84_2","first-page":"868","volume-title":"Proceedings of the European Conference on Computer Vision","author":"Zheng Liang","year":"2016","unstructured":"Liang Zheng, Zhi Bie, Yifan Sun, Jingdong Wang, Chi Su, Shengjin Wang, and Qi Tian. 2016. Mars: A video benchmark for large-scale person re-identification. In Proceedings of the European Conference on Computer Vision. Springer, 868\u2013884."},{"issue":"3","key":"e_1_3_1_85_2","doi-asserted-by":"crossref","first-page":"653","DOI":"10.1109\/TPAMI.2012.138","article-title":"Reidentification by relative distance comparison","volume":"35","author":"Zheng Wei-Shi","year":"2012","unstructured":"Wei-Shi Zheng, Shaogang Gong, and Tao Xiang. 2012. Reidentification by relative distance comparison. IEEE Transactions on Pattern Analysis and Machine Intelligence 35, 3 (2012), 653\u2013668.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"issue":"1","key":"e_1_3_1_86_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3159171","article-title":"A discriminatively learned cnn embedding for person reidentification","volume":"14","author":"Zheng Zhedong","year":"2017","unstructured":"Zhedong Zheng, Liang Zheng, and Yi Yang. 2017. A discriminatively learned cnn embedding for person reidentification. ACM Transactions on Multimedia Computing, Communications, and Applications 14, 1 (2017), 1\u201320.","journal-title":"ACM Transactions on Multimedia Computing, Communications, and Applications"},{"key":"e_1_3_1_87_2","first-page":"1318","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","author":"Zhong Zhun","year":"2017","unstructured":"Zhun Zhong, Liang Zheng, Donglin Cao, and Shaozi Li. 2017. Re-ranking person re-identification with k-reciprocal encoding. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 1318\u20131327."},{"key":"e_1_3_1_88_2","first-page":"4747","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","author":"Zhou Zhen","year":"2017","unstructured":"Zhen Zhou, Yan Huang, Wei Wang, Liang Wang, and Tieniu Tan. 2017. See the forest for the trees: Joint spatial and temporal recurrent neural networks for video-based person re-identification. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 4747\u20134756."},{"key":"e_1_3_1_89_2","first-page":"2223","volume-title":"Proceedings of the IEEE International Conference on Computer Vision","author":"Zhu Jun-Yan","year":"2017","unstructured":"Jun-Yan Zhu, Taesung Park, Phillip Isola, and Alexei A. Efros. 2017. Unpaired image-to-image translation using cycle-consistent adversarial networks. In Proceedings of the IEEE International Conference on Computer Vision. 2223\u20132232."}],"container-title":["ACM Transactions on Multimedia Computing, Communications, and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3617375","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3617375","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T16:45:54Z","timestamp":1750178754000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3617375"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,18]]},"references-count":88,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2024,2,29]]}},"alternative-id":["10.1145\/3617375"],"URL":"https:\/\/doi.org\/10.1145\/3617375","relation":{},"ISSN":["1551-6857","1551-6865"],"issn-type":[{"value":"1551-6857","type":"print"},{"value":"1551-6865","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,10,18]]},"assertion":[{"value":"2022-12-19","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-08-20","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-10-18","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}