{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T12:11:42Z","timestamp":1780488702894,"version":"3.54.1"},"reference-count":52,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Pattern Recognition"],"published-print":{"date-parts":[[2026,10]]},"DOI":"10.1016\/j.patcog.2026.113476","type":"journal-article","created":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T00:23:44Z","timestamp":1773188624000},"page":"113476","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"special_numbering":"C","title":["DiPerceiveNet: A bidirectional cross-scale perception network for vehicle re-identification"],"prefix":"10.1016","volume":"178","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-2411-4092","authenticated-orcid":false,"given":"Jihao","family":"Cai","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhiqiang","family":"He","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhi","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1170-4340","authenticated-orcid":false,"given":"Yangjie","family":"Cao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.patcog.2026.113476_bib0001","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2024.128745","article-title":"Advances in vehicle re-identification techniques: a survey","volume":"614","author":"Yi","year":"2025","journal-title":"Neurocomputing"},{"issue":"1","key":"10.1016\/j.patcog.2026.113476_bib0002","article-title":"Multi-axis compression fusion network for vehicle re-identification: T. Ma et al","volume":"15","author":"Ma","year":"2025","journal-title":"Sci. Rep."},{"issue":"5","key":"10.1016\/j.patcog.2026.113476_bib0003","doi-asserted-by":"crossref","DOI":"10.1016\/j.geits.2025.100269","article-title":"Enhancing vehicle re-identification by pair-flexible pose guided vehicle image synthesis","volume":"4","author":"Li","year":"2025","journal-title":"Green Energy Intell. Transp."},{"issue":"1","key":"10.1016\/j.patcog.2026.113476_bib0004","doi-asserted-by":"crossref","first-page":"1769","DOI":"10.32604\/cmc.2025.062950","article-title":"AG-GCN: vehicle re-identification based on attention-guided graph convolutional network","volume":"84","author":"Sun","year":"2025","journal-title":"Comput. Mater. Continua"},{"issue":"9","key":"10.1016\/j.patcog.2026.113476_bib0005","doi-asserted-by":"crossref","first-page":"11156","DOI":"10.1109\/TVT.2023.3262983","article-title":"URRNet: a unified relational reasoning network for vehicle re-identification","volume":"72","author":"Qian","year":"2023","journal-title":"IEEE Trans. Veh. Technol."},{"key":"10.1016\/j.patcog.2026.113476_bib0006","article-title":"MSFFT: multi-scale feature fusion transformer for cross platform vehicle re-identification","volume":"582","author":"Ashutosh Holla","year":"2024","journal-title":"Neurocomputing"},{"issue":"2","key":"10.1016\/j.patcog.2026.113476_bib0007","doi-asserted-by":"crossref","first-page":"1263","DOI":"10.1109\/TITS.2023.3316068","article-title":"Multi-branch enhanced discriminative network for vehicle re-identification","volume":"25","author":"Lian","year":"2023","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"10.1016\/j.patcog.2026.113476_bib0008","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2023.109304","article-title":"Detail enhancement-based vehicle re-identification with orientation-guided re-ranking","volume":"137","author":"Sun","year":"2023","journal-title":"Pattern Recognit."},{"issue":"10","key":"10.1016\/j.patcog.2026.113476_bib0009","doi-asserted-by":"crossref","first-page":"2977","DOI":"10.3390\/s25102977","article-title":"Vehicle re-identification method based on efficient self-attention CNN-transformer and multi-task learning optimization","volume":"25","author":"Wang","year":"2025","journal-title":"Sensors"},{"key":"10.1016\/j.patcog.2026.113476_bib0010","doi-asserted-by":"crossref","DOI":"10.1016\/j.jvcir.2023.103937","article-title":"Vehicle re-identification based on grouping aggregation attention and cross-part interaction","volume":"97","author":"Pang","year":"2023","journal-title":"J. Vis. Commun. Image Represent."},{"key":"10.1016\/j.patcog.2026.113476_bib0011","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.127708","article-title":"Diversified distillation fusion network for vehicle re-identification","volume":"283","author":"Zhang","year":"2025","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.patcog.2026.113476_bib0012","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2024.111266","article-title":"Multi-scale hierarchical feature fusion network for change detection","volume":"161","author":"Zheng","year":"2025","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2026.113476_bib0013","series-title":"2024 International Conference on Image Processing, Computer Vision and Machine Learning (ICICML)","first-page":"294","article-title":"Image quality assessment characteristics for super-resolution","author":"Li","year":"2024"},{"issue":"1","key":"10.1016\/j.patcog.2026.113476_bib0014","article-title":"VERI-D: a new dataset and method for multi-camera vehicle re-identification of damaged cars under varying lighting conditions","volume":"2","author":"Liu","year":"2024","journal-title":"APL Mach. Learn."},{"key":"10.1016\/j.patcog.2026.113476_bib0015","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1109\/OJITS.2025.3538037","article-title":"Vehicle re-identification and tracking: algorithmic approach, challenges and future directions","volume":"6","author":"Ashutosh Holla","year":"2025","journal-title":"IEEE Open J. Intell. Trans. Syst."},{"key":"10.1016\/j.patcog.2026.113476_bib0016","article-title":"Multi-scale feature sharing and collaborative sampling for unsupervised vehicle re-identification","volume":"172","author":"Li","year":"2026","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2026.113476_bib0017","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2024.109568","article-title":"Region-guided spatial feature aggregation network for vehicle re-identification","volume":"139","author":"Xiong","year":"2025","journal-title":"Eng. Appl. Artif. Intell."},{"issue":"1","key":"10.1016\/j.patcog.2026.113476_bib0018","doi-asserted-by":"crossref","first-page":"1947","DOI":"10.1177\/03611981241258753","article-title":"CTAFFNet: CNN\u2013transformer adaptive feature fusion object detection algorithm for complex traffic scenarios","volume":"2679","author":"Dong","year":"2025","journal-title":"Transp. Res. Rec."},{"key":"10.1016\/j.patcog.2026.113476_bib0019","unstructured":"D. Bolya, P.-Y. Huang, P. Sun, J.H. Cho, A. Madotto, C. Wei, T. Ma, J. Zhi, J. Rajasegaran, H. Rasheed, J. Wang, M. Monteiro, H. Xu, S. Dong, N. Ravi, D. Li, P. Doll\u00e1r, C. Feichtenhofer, Perception encoder: the best visual embeddings are not at the output of the network, 2025, arxiv: 2504.13181."},{"key":"10.1016\/j.patcog.2026.113476_bib0020","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2024.111072","article-title":"CEDNet: a cascade encoder\u2013decoder network for dense prediction","volume":"158","author":"Zhang","year":"2025","journal-title":"Pattern Recognit."},{"issue":"1","key":"10.1016\/j.patcog.2026.113476_bib0021","doi-asserted-by":"crossref","first-page":"2027","DOI":"10.1038\/s41598-024-52225-x","article-title":"A novel dual-pooling attention module for UAV vehicle re-identification","volume":"14","author":"Guo","year":"2024","journal-title":"Sci. Rep."},{"key":"10.1016\/j.patcog.2026.113476_bib0022","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2025.111453","article-title":"Adaptive division and priori reinforcement part learning network for vehicle re-identification","volume":"163","author":"Zhou","year":"2025","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2026.113476_bib0023","series-title":"SoutheastCon 2025","first-page":"1288","article-title":"Evaluating visual transformers for wafer defect detection: a feasibility study","author":"Lafrance","year":"2025"},{"key":"10.1016\/j.patcog.2026.113476_bib0024","series-title":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","first-page":"1","article-title":"LKA-ReID:vehicle re-identification with large kernel attention","author":"Xiang","year":"2025"},{"key":"10.1016\/j.patcog.2026.113476_bib0025","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2024.108448","article-title":"TANet: text region attention learning for vehicle re-identification","volume":"133","author":"Hu","year":"2024","journal-title":"Eng. Appl. Artif. Intell."},{"issue":"10","key":"10.1016\/j.patcog.2026.113476_bib0026","doi-asserted-by":"crossref","first-page":"19557","DOI":"10.1109\/TITS.2022.3166463","article-title":"MsKAT: multi-scale knowledge-aware transformer for vehicle re-identification","volume":"23","author":"Li","year":"2022","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"10.1016\/j.patcog.2026.113476_bib0027","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","first-page":"4701","article-title":"VehicleMAE: view-asymmetry mutual learning for vehicle re-identification pre-training via masked autoencoders","author":"Wang","year":"2025"},{"key":"10.1016\/j.patcog.2026.113476_bib0028","doi-asserted-by":"crossref","DOI":"10.1016\/j.imavis.2024.104972","article-title":"Multi-axis interactive multidimensional attention network for vehicle re-identification","volume":"144","author":"Pang","year":"2024","journal-title":"Image Vis. Comput."},{"key":"10.1016\/j.patcog.2026.113476_bib0029","first-page":"1","article-title":"Global\u2013local discriminative representation learning network for viewpoint-aware vehicle re-identification in intelligent transportation","volume":"72","author":"Chen","year":"2023","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"10.1016\/j.patcog.2026.113476_bib0030","series-title":"A Brief Excursion into Human Cognition: The Evolving Influence of Social Media & Artificial Intelligence","first-page":"17","article-title":"Perception and attention","author":"Kankam","year":"2025"},{"key":"10.1016\/j.patcog.2026.113476_bib0031","doi-asserted-by":"crossref","first-page":"692","DOI":"10.1016\/j.neunet.2023.07.048","article-title":"Visual information processing through the interplay between fine and coarse signal pathways","volume":"166","author":"Zou","year":"2023","journal-title":"Neural Netw."},{"key":"10.1016\/j.patcog.2026.113476_bib0032","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"128","article-title":"OverLoCK: an overview-first-look-closely-next ConvNet with context-mixing dynamic kernels","author":"Lou","year":"2025"},{"issue":"1","key":"10.1016\/j.patcog.2026.113476_bib0033","doi-asserted-by":"crossref","first-page":"4","DOI":"10.3390\/aisens1010004","article-title":"CORE-ReID V2: advancing the domain adaptation for object re-Identification with optimized training and ensemble fusion","volume":"1","author":"Nguyen","year":"2025","journal-title":"AI Sens."},{"issue":"1","key":"10.1016\/j.patcog.2026.113476_bib0034","first-page":"53","article-title":"Vehicle re-identification based on wavelet feature enhancement and global-local differential attention fusion","volume":"2","author":"Zhu","year":"2025","journal-title":"J. Comput. Sci. Artif. Intell."},{"issue":"11","key":"10.1016\/j.patcog.2026.113476_bib0035","doi-asserted-by":"crossref","first-page":"1917","DOI":"10.3390\/rs17111917","article-title":"SEMA-YOLO: lightweight small object detection in remote sensing image via shallow-layer enhancement and multi-scale adaptation","volume":"17","author":"Wu","year":"2025","journal-title":"Remote Sens."},{"key":"10.1016\/j.patcog.2026.113476_bib0036","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2025.112682","article-title":"Visual object tracking via adaptive feature fusion and two-stage channel selection","volume":"172","author":"Nai","year":"2026","journal-title":"Pattern Recognit."},{"issue":"14","key":"10.1016\/j.patcog.2026.113476_bib0037","doi-asserted-by":"crossref","first-page":"26898","DOI":"10.1109\/JIOT.2025.3561186","article-title":"PEFN: a patches enhancement and hierarchical fusion network for robust vehicle reidentification","volume":"12","author":"He","year":"2025","journal-title":"IEEE Internet Things J."},{"key":"10.1016\/j.patcog.2026.113476_bib0038","series-title":"2016 IEEE International Conference on Multimedia and Expo (ICME)","first-page":"1","article-title":"Large-scale vehicle re-identification in urban surveillance videos","author":"Liu","year":"2016"},{"key":"10.1016\/j.patcog.2026.113476_bib0039","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","first-page":"2167","article-title":"Deep relative distance learning: tell the difference between similar vehicles","author":"Liu","year":"2016"},{"key":"10.1016\/j.patcog.2026.113476_bib0040","doi-asserted-by":"crossref","unstructured":"Z. Tang, M. Naphade, M.-Y. Liu, X. Yang, S. Birchfield, S. Wang, R. Kumar, D. Anastasiu, J.-N. Hwang, CityFlow: a city-scale benchmark for multi-target multi-camera vehicle tracking and re-identification, in: Proc. CVPR, Long Beach, CA, USA, 2019, pp. 8797\u20138806.","DOI":"10.1109\/CVPR.2019.00900"},{"key":"10.1016\/j.patcog.2026.113476_bib0041","series-title":"Proceedings of the IEEE International Conference on Computer Vision","first-page":"1900","article-title":"Learning deep neural networks for vehicle re-ID with visual-spatio-temporal path proposals","author":"Shen","year":"2017"},{"issue":"10","key":"10.1016\/j.patcog.2026.113476_bib0042","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","year":"2020","journal-title":"IEEE Trans. Multimedia."},{"key":"10.1016\/j.patcog.2026.113476_bib0043","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2024.111455","article-title":"AIVR-Net: attribute-based invariant visual representation learning for vehicle re-identification","volume":"289","author":"Zhang","year":"2024","journal-title":"Knowl. Based Syst."},{"issue":"13","key":"10.1016\/j.patcog.2026.113476_bib0044","doi-asserted-by":"crossref","first-page":"7041","DOI":"10.3390\/app15137041","article-title":"Learning part-based features for vehicle re-identification with global context","volume":"15","author":"Nath","year":"2025","journal-title":"Appl. Sci."},{"issue":"1","key":"10.1016\/j.patcog.2026.113476_bib0045","article-title":"Learning super-resolution and pyramidal convolution residual network for vehicle re-identification","volume":"14","author":"Liu","year":"2024","journal-title":"Sci. Rep."},{"key":"10.1016\/j.patcog.2026.113476_bib0046","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2022.109258","article-title":"A dual self-attention mechanism for vehicle re-identification","volume":"137","author":"Zhu","year":"2023","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2026.113476_bib0047","series-title":"2024 IEEE Intelligent Vehicles Symposium (IV)","first-page":"447","article-title":"VehicleGAN: pair-flexible pose guided image synthesis for vehicle re-identification","author":"Li","year":"2024"},{"key":"10.1016\/j.patcog.2026.113476_bib0048","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2023.110526","article-title":"Coarse-to-fine sparse self-attention for vehicle re-identification","volume":"270","author":"Huang","year":"2023","journal-title":"Knowl. Based Syst."},{"key":"10.1016\/j.patcog.2026.113476_bib0049","doi-asserted-by":"crossref","first-page":"1039","DOI":"10.1109\/TIP.2023.3238642","article-title":"GiT: graph interactive transformer for vehicle re-identification","volume":"32","author":"Shen","year":"2023","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.patcog.2026.113476_bib0050","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"22119","article-title":"SeCap: self-calibrating and adaptive prompts for cross-view person re-Identification in aerial-ground networks","author":"Wang","year":"2025"},{"issue":"4","key":"10.1016\/j.patcog.2026.113476_bib0051","doi-asserted-by":"crossref","first-page":"1853","DOI":"10.1007\/s00530-023-01077-y","article-title":"View-aware attribute-guided network for vehicle re-identification","volume":"29","author":"Tumrani","year":"2023","journal-title":"Multimedia Syst."},{"key":"10.1016\/j.patcog.2026.113476_bib0052","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1016\/j.neunet.2023.10.032","article-title":"Heterogeneous context interaction network for vehicle re-identification","volume":"169","author":"Sun","year":"2024","journal-title":"Neural Netw."}],"container-title":["Pattern Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0031320326004425?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0031320326004425?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T17:02:55Z","timestamp":1779382975000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0031320326004425"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10]]},"references-count":52,"alternative-id":["S0031320326004425"],"URL":"https:\/\/doi.org\/10.1016\/j.patcog.2026.113476","relation":{},"ISSN":["0031-3203"],"issn-type":[{"value":"0031-3203","type":"print"}],"subject":[],"published":{"date-parts":[[2026,10]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"DiPerceiveNet: A bidirectional cross-scale perception network for vehicle re-identification","name":"articletitle","label":"Article Title"},{"value":"Pattern Recognition","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.patcog.2026.113476","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"113476"}}