{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T22:59:10Z","timestamp":1768345150326,"version":"3.49.0"},"reference-count":48,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T00:00:00Z","timestamp":1768262400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Nantong Basic Science Research Program","award":["JC2023021"],"award-info":[{"award-number":["JC2023021"]}]},{"name":"Doctoral Research Startup Fund of Nantong University","award":["25B03"],"award-info":[{"award-number":["25B03"]}]},{"name":"Qing Lan Project of Jiangsu Province"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Imaging"],"abstract":"<jats:p>Cross-modality person re-identification faces challenges such as illumination discrepancies, local occlusions, and inconsistent modality structures, leading to misalignment and sensitivity issues. We propose GLCN, a framework that addresses these problems by enhancing representation learning through locality enhancement, cross-modality structural alignment, and intra-modality compactness. Key components include the Locality-Preserved Cross-branch Fusion (LPCF) module, which combines Local\u2013Positional\u2013Channel Gating (LPCG) for local region and positional sensitivity; Cross-branch Context Interpolated Attention (CCIA) for stable cross-branch consistency; and Graph-Enhanced Center Geometry Alignment (GE-CGA), which aligns class-center similarity structures across modalities to preserve category-level relationships. We also introduce Intra-Modal Prototype Discrepancy Mining Loss (IPDM-Loss) to reduce intra-class variance and improve inter-class separation, thereby creating more compact identity structures in both RGB and IR spaces. Extensive experiments on SYSU-MM01, RegDB, and other benchmarks demonstrate the effectiveness of our approach.<\/jats:p>","DOI":"10.3390\/jimaging12010042","type":"journal-article","created":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T15:52:57Z","timestamp":1768319577000},"page":"42","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["GLCN: Graph-Aware Locality-Enhanced Cross-Modality Re-ID Network"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-1677-3636","authenticated-orcid":false,"given":"Junjie","family":"Cao","sequence":"first","affiliation":[{"name":"School of Artificial Intelligence and Computer Science, Nantong University, Nantong 226019, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-9073-8604","authenticated-orcid":false,"given":"Yuhang","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence and Computer Science, Nantong University, Nantong 226019, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-8402-3068","authenticated-orcid":false,"given":"Rong","family":"Rong","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence and Computer Science, Nantong University, Nantong 226019, China"}]},{"given":"Xing","family":"Xie","sequence":"additional","affiliation":[{"name":"Engineering Training Center, Nantong University, Nantong 226019, China"}]}],"member":"1968","published-online":{"date-parts":[[2026,1,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2872","DOI":"10.1109\/TPAMI.2021.3054775","article-title":"Deep learning for person re-identification: A survey and outlook","volume":"44","author":"Ye","year":"2021","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2410","DOI":"10.1007\/s11263-024-02284-4","article-title":"Transformer for object re-identification: A survey","volume":"133","author":"Ye","year":"2025","journal-title":"Int. J. Comput. Vis."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"5821","DOI":"10.1109\/TCSVT.2025.3531142","article-title":"Mask-Aware Hierarchical Aggregation Transformer for Occluded Person Re-identification","volume":"35","author":"Zhang","year":"2025","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"ref_4","unstructured":"Yu, H., Cheng, X., Peng, W., Liu, W., and Zhao, G. (, January 1\u20136). Modality unifying network for visible-infrared person re-identification. Proceedings of the IEEE\/CVF International Conference on Computer Vision, Paris, France."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1007\/s44267-023-00032-9","article-title":"Visible-infrared person re-identification via specific and shared representations learning","volume":"1","author":"Zheng","year":"2023","journal-title":"Vis. Intell."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Zhang, Q., Lai, C., Liu, J., Huang, N., and Han, J. (2022, January 18\u201324). Fmcnet: Feature-level modality compensation for visible-infrared person re-identification. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, New Orleans, LA, USA.","DOI":"10.1109\/CVPR52688.2022.00720"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Yang, B., Chen, J., and Ye, M. (2023, January 1\u20136). Towards grand unified representation learning for unsupervised visible-infrared person re-identification. Proceedings of the IEEE\/CVF International Conference on Computer Vision, Paris, France.","DOI":"10.1109\/ICCV51070.2023.01016"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"111756","DOI":"10.1016\/j.patcog.2025.111756","article-title":"Shape-centered representation learning for visible-infrared person re-identification","volume":"167","author":"Li","year":"2025","journal-title":"Pattern Recognit."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Kim, M., Kim, S., Park, J., Park, S., and Sohn, K. (2023, January 17\u201324). Partmix: Regularization strategy to learn part discovery for visible-infrared person re-identification. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Vancouver, BC, Canada.","DOI":"10.1109\/CVPR52729.2023.01786"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Fang, X., Yang, Y., and Fu, Y. (2023, January 1\u20136). Visible-infrared person re-identification via semantic alignment and affinity inference. Proceedings of the IEEE\/CVF International Conference on Computer Vision, Paris, France.","DOI":"10.1109\/ICCV51070.2023.01035"},{"key":"ref_11","first-page":"1034","article-title":"Modality-adaptive mixup and invariant decomposition for RGB-infrared person re-identification","volume":"36","author":"Huang","year":"2022","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"126652","DOI":"10.1016\/j.neucom.2023.126652","article-title":"On exploring pose estimation as an auxiliary learning task for visible\u2013infrared person re-identification","volume":"556","author":"Miao","year":"2023","journal-title":"Neurocomputing"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Sun, H., Liu, J., Zhang, Z., Wang, C., Qu, Y., Xie, Y., and Ma, L. (2022, January 10\u201314). Not all pixels are matched: Dense contrastive learning for cross-modality person re-identification. Proceedings of the 30th ACM International Conference on Multimedia, Lisboa, Portugal.","DOI":"10.1145\/3503161.3547970"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3723358","article-title":"Local-Aware Residual Attention Vision Transformer for Visible-Infrared Person Re-Identification","volume":"146","author":"Hua","year":"2025","journal-title":"ACM Trans. Multimed. Comput. Commun. Appl."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Wu, Z., and Ye, M. (2023, January 17\u201324). Unsupervised visible-infrared person re-identification via progressive graph matching and alternate learning. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Vancouver, BC, Canada.","DOI":"10.1109\/CVPR52729.2023.00921"},{"key":"ref_16","first-page":"4596","article-title":"High-order structure based middle-feature learning for visible-infrared person re-identification","volume":"38","author":"Qiu","year":"2024","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"12032","DOI":"10.1109\/TCSVT.2024.3425536","article-title":"Multi-stage auxiliary learning for visible-infrared person re-identification","volume":"34","author":"Zhang","year":"2024","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"7063","DOI":"10.1007\/s00371-024-03792-7","article-title":"Bridging visible and infrared modalities: A dual-level joint align network for person re-identification","volume":"41","author":"Hu","year":"2025","journal-title":"Vis. Comput."},{"key":"ref_19","unstructured":"Dosovitskiy, A. (2020). An image is worth 16x16 words: Transformers for image recognition at scale. arXiv."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Ni, H., Li, Y., Gao, L., Shen, H.T., and Song, J. (2023, January 1\u20136). Part-aware transformer for generalizable person re-identification. Proceedings of the IEEE\/CVF International Conference on Computer Vision, Paris, France.","DOI":"10.1109\/ICCV51070.2023.01036"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"103898","DOI":"10.1016\/j.jvcir.2023.103898","article-title":"Transformer-based global\u2013local feature learning model for occluded person re-identification","volume":"95","author":"Zhang","year":"2023","journal-title":"J. Vis. Commun. Image Represent."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Zhou, J., Dong, Q., Zhang, Z., Liu, S., and Durrani, T.S. (2023). Cross-modality person re-identification via local paired graph attention network. Sensors, 23.","DOI":"10.3390\/s23084011"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1023\/A:1010091220143","article-title":"The cross-entropy method for combinatorial and continuous optimization","volume":"1","author":"Rubinstein","year":"1999","journal-title":"Methodol. Comput. Appl. Probab."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Schroff, F., Kalenichenko, D., and Philbin, J. (2015, January 7\u201312). Facenet: A unified embedding for face recognition and clustering. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Boston, MA, USA.","DOI":"10.1109\/CVPR.2015.7298682"},{"key":"ref_25","first-page":"425","article-title":"Cross-modality person re-identification with memory-based contrastive embedding","volume":"37","author":"Cheng","year":"2023","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"ref_26","first-page":"91","article-title":"Faster r-cnn: Towards real-time object detection with region proposal networks","volume":"28","author":"Ren","year":"2015","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Wu, A., Zheng, W.S., Yu, H.X., Gong, S., and Lai, J. (2017, January 22\u201329). RGB-infrared cross-modality person re-identification. Proceedings of the IEEE International Conference on Computer Vision, Venice, Italy.","DOI":"10.1109\/ICCV.2017.575"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Nguyen, D.T., Hong, H.G., Kim, K.W., and Park, K.R. (2017). Person recognition system based on a combination of body images from visible light and thermal cameras. Sensors, 17.","DOI":"10.3390\/s17030605"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Zhang, Y., and Wang, H. (2023, January 17\u201324). Diverse embedding expansion network and low-light cross-modality benchmark for visible-infrared person re-identification. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Vancouver, BC, Canada.","DOI":"10.1109\/CVPR52729.2023.00214"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Li, W., Zhao, R., Xiao, T., and Wang, X. (2014, January 23\u201328). Deepreid: Deep filter pairing neural network for person re-identification. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Columbus, OH, USA.","DOI":"10.1109\/CVPR.2014.27"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Xiao, T., Li, H., Ouyang, W., and Wang, X. (2016, January 27\u201330). Learning deep feature representations with domain guided dropout for person re-identification. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, NV, USA.","DOI":"10.1109\/CVPR.2016.140"},{"key":"ref_32","first-page":"1835","article-title":"Learning progressive modality-shared transformers for effective visible-infrared person re-identification","volume":"37","author":"Lu","year":"2023","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Wu, J., Liu, H., Su, Y., Shi, W., and Tang, H. (2023, January 1\u20136). Learning concordant attention via target-aware alignment for visible-infrared person re-identification. Proceedings of the IEEE\/CVF International Conference on Computer Vision, Paris, France.","DOI":"10.1109\/ICCV51070.2023.01021"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"8172","DOI":"10.1109\/TMM.2024.3377139","article-title":"Cooperative separation of modality shared-specific features for visible-infrared person re-identification","volume":"26","author":"Yang","year":"2024","journal-title":"IEEE Trans. Multimed."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"2299","DOI":"10.1109\/TPAMI.2023.3332875","article-title":"Channel augmentation for visible-infrared re-identification","volume":"46","author":"Ye","year":"2023","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"2361","DOI":"10.1109\/TCSVT.2023.3309647","article-title":"Enhanced invariant feature joint learning via modality-invariant neighbor relations for cross-modality person re-identification","volume":"34","author":"Du","year":"2023","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"4503","DOI":"10.1109\/TCSVT.2023.3340225","article-title":"Correlation-guided semantic consistency network for visible-infrared person re-identification","volume":"34","author":"Li","year":"2023","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"7754","DOI":"10.1109\/TII.2024.3359432","article-title":"Diverse-feature collaborative progressive learning for visible-infrared person re-identification","volume":"20","author":"Chan","year":"2024","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"5494","DOI":"10.1109\/TNNLS.2024.3384023","article-title":"Disentangling modality and posture factors: Memory-attention and orthogonal decomposition for visible-infrared person re-identification","volume":"36","author":"Lu","year":"2024","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"3400","DOI":"10.1109\/TIFS.2025.3541969","article-title":"Adaptive generation of privileged intermediate information for visible-infrared person re-identification","volume":"20","author":"Alehdaghi","year":"2025","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"568","DOI":"10.1109\/TMM.2024.3521843","article-title":"Cross-Modality Semantic Consistency Learning for Visible-Infrared Person Re-Identification","volume":"27","author":"Liu","year":"2024","journal-title":"IEEE Trans. Multimed."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"2015","DOI":"10.1109\/TMM.2024.3521822","article-title":"MDANet: Modality-Aware Domain Alignment Network for Visible-Infrared Person Re-Identification","volume":"27","author":"Cheng","year":"2024","journal-title":"IEEE Trans. Multimed."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"111090","DOI":"10.1016\/j.patcog.2024.111090","article-title":"Mscmnet: Multi-scale semantic correlation mining for visible-infrared person re-identification","volume":"159","author":"Hua","year":"2025","journal-title":"Pattern Recognit."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"4137","DOI":"10.1109\/TMM.2025.3535353","article-title":"Clip-driven semantic discovery network for visible-infrared person re-identification","volume":"27","author":"Yu","year":"2025","journal-title":"IEEE Trans. Multimed."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Ye, M., Shen, J., J. Crandall, D., Shao, L., and Luo, J. (2020, January 23\u201328). Dynamic dual-attentive aggregation learning for visible-infrared person re-identification. Proceedings of the European Conference on Computer Vision, Glasgow, UK.","DOI":"10.1007\/978-3-030-58520-4_14"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Yang, M., Huang, Z., Hu, P., Li, T., Lv, J., and Peng, X. (2022, January 18\u201324). Learning with twin noisy labels for visible-infrared person re-identification. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, New Orleans, LA, USA.","DOI":"10.1109\/CVPR52688.2022.01391"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"104265","DOI":"10.1016\/j.jvcir.2024.104265","article-title":"A visible-infrared person re-identification method based on meta-graph isomerization aggregation module","volume":"104","author":"Chongrui","year":"2024","journal-title":"J. Vis. Commun. Image Represent."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"8086","DOI":"10.1109\/TCSVT.2025.3560118","article-title":"Enhancing Visible-Infrared Person Re-identification with Modality- and Instance-aware Adaptation Learning","volume":"35","author":"Wu","year":"2025","journal-title":"IEEE Trans. Circuits Syst. Video Technol."}],"container-title":["Journal of Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2313-433X\/12\/1\/42\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T16:15:12Z","timestamp":1768320912000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2313-433X\/12\/1\/42"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,13]]},"references-count":48,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,1]]}},"alternative-id":["jimaging12010042"],"URL":"https:\/\/doi.org\/10.3390\/jimaging12010042","relation":{},"ISSN":["2313-433X"],"issn-type":[{"value":"2313-433X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1,13]]}}}