{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T16:03:30Z","timestamp":1780070610962,"version":"3.54.0"},"reference-count":49,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"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":["Neural Networks"],"published-print":{"date-parts":[[2026,11]]},"DOI":"10.1016\/j.neunet.2026.109137","type":"journal-article","created":{"date-parts":[[2026,5,16]],"date-time":"2026-05-16T15:28:28Z","timestamp":1778945308000},"page":"109137","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["MGCFI-Net: Multi-scale globally aware feature learning with cross-view feature interaction for multi-view stereo"],"prefix":"10.1016","volume":"203","author":[{"given":"Ming","family":"Han","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4226-4368","authenticated-orcid":false,"given":"Hui","family":"Yin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aixin","family":"Chong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0852-6907","authenticated-orcid":false,"given":"Hua","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.neunet.2026.109137_bib0001","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1007\/s11263-016-0902-9","article-title":"Large-scale data for multiple-view stereopsis","volume":"120","author":"Aan\u00e6s","year":"2016","journal-title":"International Journal of Computer Vision"},{"issue":"4","key":"10.1016\/j.neunet.2026.109137_bib0002","doi-asserted-by":"crossref","first-page":"4289","DOI":"10.1007\/s10489-022-03754-3","article-title":"MFNet: Multi-level fusion aware feature pyramid based multi-view stereo network for 3D reconstruction","volume":"53","author":"Cai","year":"2023","journal-title":"Applied Intelligence"},{"key":"10.1016\/j.neunet.2026.109137_bib0003","series-title":"European conference on computer vision","first-page":"205","article-title":"Swin-Unet: Unet-like pure transformer for medical image segmentation","author":"Cao","year":"2022"},{"key":"10.1016\/j.neunet.2026.109137_bib0004","doi-asserted-by":"crossref","DOI":"10.1109\/TIP.2023.3347929","article-title":"EI-MVSNet: Epipolar-guided multi-view stereo network with interval-aware label","author":"Chang","year":"2024","journal-title":"IEEE Transactions on Image Processing"},{"key":"10.1016\/j.neunet.2026.109137_bib0005","first-page":"1","article-title":"Multiview stereo via noise suppression patchmatch","volume":"73","author":"Chen","year":"2024","journal-title":"IEEE Transactions on Instrumentation and Measurement"},{"issue":"12","key":"10.1016\/j.neunet.2026.109137_bib0006","doi-asserted-by":"crossref","first-page":"12396","DOI":"10.1109\/TCSVT.2025.3578452","article-title":"Learning multi-view stereo with geometry-aware prior","volume":"35","author":"Chen","year":"2025","journal-title":"IEEE Transactions on Circuits and Systems for Video Technology"},{"key":"10.1016\/j.neunet.2026.109137_bib0007","unstructured":"Chen, L.-C., Papandreou, G., Schroff, F., & Adam, H. (2017). Rethinking atrous convolution for semantic image segmentation. arXiv preprint arXiv: 1706.05587."},{"key":"10.1016\/j.neunet.2026.109137_bib0008","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"2524","article-title":"Deep stereo using adaptive thin volume representation with uncertainty awareness","author":"Cheng","year":"2020"},{"key":"10.1016\/j.neunet.2026.109137_bib0009","series-title":"Proceedings of the IEEE international conference on computer vision","first-page":"764","article-title":"Deformable convolutional networks","author":"Dai","year":"2017"},{"key":"10.1016\/j.neunet.2026.109137_bib0010","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"8585","article-title":"TransMVSNet: Global context-aware multi-view stereo network with transformers","author":"Ding","year":"2022"},{"key":"10.1016\/j.neunet.2026.109137_bib0011","series-title":"Proceedings of the IEEE international conference on computer vision","first-page":"873","article-title":"Massively parallel multiview stereopsis by surface normal diffusion","author":"Galliani","year":"2015"},{"key":"10.1016\/j.neunet.2026.109137_bib0012","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"2495","article-title":"Cascade cost volume for high-resolution multi-view stereo and stereo matching","author":"Gu","year":"2020"},{"issue":"17","key":"10.1016\/j.neunet.2026.109137_bib0013","doi-asserted-by":"crossref","first-page":"7924","DOI":"10.1007\/s10489-024-05574-z","article-title":"Enhanced feature pyramid for multi- view stereo with adaptive correlation cost volume","volume":"54","author":"Han","year":"2024","journal-title":"Applied Intelligence"},{"key":"10.1016\/j.neunet.2026.109137_bib0014","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2025.107568","article-title":"Fast underwater scene reconstruction using multi-view stereo and physical imaging","author":"Hu","year":"2025","journal-title":"Neural Networks"},{"key":"10.1016\/j.neunet.2026.109137_bib0015","series-title":"Proceedings of the IEEE\/CVF international conference on computer vision (ICCV)","first-page":"27806","article-title":"MonoMVSNet: Monocular priors guided multi-view stereo network","author":"Jiang","year":"2025"},{"issue":"4","key":"10.1016\/j.neunet.2026.109137_bib0016","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3072959.3073599","article-title":"Tanks and temples: Benchmarking large-scale scene reconstruction","volume":"36","author":"Knapitsch","year":"2017","journal-title":"ACM Transactions on Graphics (ToG)"},{"key":"10.1016\/j.neunet.2026.109137_bib0017","first-page":"8564","article-title":"WT-MVSNet: Window-based transformers for multi-view stereo","volume":"35","author":"Liao","year":"2022","journal-title":"Advances in Neural Information Processing Systems"},{"key":"10.1016\/j.neunet.2026.109137_bib0018","series-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","first-page":"2117","article-title":"Feature pyramid networks for object detection","author":"Lin","year":"2017"},{"key":"10.1016\/j.neunet.2026.109137_bib0019","series-title":"Proceedings of the IEEE\/CVF international conference on computer vision","first-page":"18088","article-title":"When epipolar constraint meets non-local operators in multi-view stereo","author":"Liu","year":"2023"},{"key":"10.1016\/j.neunet.2026.109137_bib0020","series-title":"Proceedings of the IEEE\/CVF international conference on computer vision","first-page":"10012","article-title":"Swin transformer: Hierarchical vision transformer using shifted windows","author":"Liu","year":"2021"},{"key":"10.1016\/j.neunet.2026.109137_bib0021","series-title":"Proceedings of the IEEE\/CVF international conference on computer vision","first-page":"5732","article-title":"EPP-MVSNet: Epipolar-assembling based depth prediction for multi-view stereo","author":"Ma","year":"2021"},{"key":"10.1016\/j.neunet.2026.109137_bib0022","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"12991","article-title":"Generalized binary search network for highly-efficient multi-view stereo","author":"Mi","year":"2022"},{"key":"10.1016\/j.neunet.2026.109137_bib0023","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"8645","article-title":"Rethinking depth estimation for multi-view stereo: A unified representation","author":"Peng","year":"2022"},{"key":"10.1016\/j.neunet.2026.109137_bib0024","series-title":"Medical image computing and computer-assisted intervention\u2013MICCAI 2015: 18th international conference, Munich, Germany, October 5-9, 2015, proceedings, part III 18","first-page":"234","article-title":"U-net: Convolutional networks for biomedical image segmentation","author":"Ronneberger","year":"2015"},{"key":"10.1016\/j.neunet.2026.109137_bib0025","series-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","first-page":"4104","article-title":"Structure-from-motion revisited","author":"Schonberger","year":"2016"},{"key":"10.1016\/j.neunet.2026.109137_bib0026","series-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","first-page":"3260","article-title":"A multi-view stereo benchmark with high-resolution images and multi-camera videos","author":"Schops","year":"2017"},{"key":"10.1016\/j.neunet.2026.109137_bib0027","series-title":"Proceedings of the AAAI conference on artificial intelligence","first-page":"2348","article-title":"Efficient edge-preserving multi-view stereo network for depth estimation","volume":"vol. 37","author":"Su","year":"2023"},{"issue":"6","key":"10.1016\/j.neunet.2026.109137_bib0028","doi-asserted-by":"crossref","first-page":"3367","DOI":"10.1007\/s11263-024-02337-8","article-title":"Context-aware multi-view stereo network for efficient edge-preserving depth estimation","volume":"133","author":"Su","year":"2025","journal-title":"International Journal of Computer Vision"},{"key":"10.1016\/j.neunet.2026.109137_bib0029","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"8922","article-title":"LoFTR: Detector-free local feature matching with transformers","author":"Sun","year":"2021"},{"key":"10.1016\/j.neunet.2026.109137_bib0030","first-page":"5998","article-title":"Attention is all you need","volume":"30","author":"Vaswani","year":"2017","journal-title":"Advances in Neural Information Processing Systems"},{"key":"10.1016\/j.neunet.2026.109137_bib0031","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"8606","article-title":"IterMVS: Iterative probability estimation for efficient multi-view stereo","author":"Wang","year":"2022"},{"key":"10.1016\/j.neunet.2026.109137_bib0032","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2024.129066","article-title":"Transformer-guided feature pyramid network for multi-view stereo","volume":"617","author":"Wang","year":"2025","journal-title":"Neurocomputing"},{"issue":"10","key":"10.1016\/j.neunet.2026.109137_bib0033","doi-asserted-by":"crossref","first-page":"9414","DOI":"10.1109\/TCSVT.2024.3398060","article-title":"Efficient multi-view stereo by dynamic cost volume and cross-scale propagation","volume":"34","author":"Wang","year":"2024","journal-title":"IEEE Transactions on Circuits and Systems for Video Technology"},{"key":"10.1016\/j.neunet.2026.109137_bib0034","series-title":"European conference on computer vision","first-page":"573","article-title":"MVSter: Epipolar transformer for efficient multi-view stereo","author":"Wang","year":"2022"},{"key":"10.1016\/j.neunet.2026.109137_bib0035","first-page":"1","article-title":"LoliMVS: An end-to-end network for multiview stereo with low-light images","volume":"73","author":"Wang","year":"2024","journal-title":"IEEE Transactions on Instrumentation and Measurement"},{"key":"10.1016\/j.neunet.2026.109137_bib0036","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"20207","article-title":"GOMVS: Geometrically consistent cost aggregation for multi-view stereo","author":"Wu","year":"2024"},{"key":"10.1016\/j.neunet.2026.109137_bib0037","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2025.107591","article-title":"Real-time and accurate stereo matching via tri-fusion volume for stereo vision","volume":"189","author":"Xu","year":"2025","journal-title":"Neural Networks"},{"key":"10.1016\/j.neunet.2026.109137_bib0038","series-title":"Proceedings of the IEEE\/CVF international conference on computer vision","first-page":"6078","article-title":"Digging into uncertainty in self-supervised multi-view stereo","author":"Xu","year":"2021"},{"key":"10.1016\/j.neunet.2026.109137_bib0039","series-title":"Proceedings of the AAAI conference on artificial intelligence","first-page":"12508","article-title":"Learning inverse depth regression for multi-view stereo with correlation cost volume","volume":"vol. 34","author":"Xu","year":"2020"},{"key":"10.1016\/j.neunet.2026.109137_bib0040","series-title":"European conference on computer vision","first-page":"674","article-title":"Dense hybrid recurrent multi-view stereo net with dynamic consistency checking","author":"Yan","year":"2020"},{"key":"10.1016\/j.neunet.2026.109137_bib0041","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"4877","article-title":"Cost volume pyramid based depth inference for multi-view stereo","author":"Yang","year":"2020"},{"key":"10.1016\/j.neunet.2026.109137_bib0042","series-title":"Proceedings of the European conference on computer vision (ECCV)","first-page":"767","article-title":"MVSNet: Depth inference for unstructured multi-view stereo","author":"Yao","year":"2018"},{"key":"10.1016\/j.neunet.2026.109137_bib0043","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"5525","article-title":"Recurrent MVSNet for high-resolution multi-view stereo depth inference","author":"Yao","year":"2019"},{"key":"10.1016\/j.neunet.2026.109137_bib0044","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"1790","article-title":"BlendedMVS: A large-scale dataset for generalized multi-view stereo networks","author":"Yao","year":"2020"},{"key":"10.1016\/j.neunet.2026.109137_bib0045","series-title":"European conference on computer vision","first-page":"766","article-title":"Pyramid multi-view stereo net with self-adaptive view aggregation","author":"Yi","year":"2020"},{"issue":"1","key":"10.1016\/j.neunet.2026.109137_bib0046","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1007\/s11263-022-01697-3","article-title":"Vis-MVSNet: Visibility-aware multi-view stereo network","volume":"131","author":"Zhang","year":"2023","journal-title":"International Journal of Computer Vision"},{"key":"10.1016\/j.neunet.2026.109137_bib0047","doi-asserted-by":"crossref","unstructured":"Zhang, J., Yao, Y., Li, S., Luo, Z., & Fang, T. (2020). Visibility-aware multi-view stereo network. arXiv preprint arXiv: 2008.07928.","DOI":"10.5244\/C.34.109"},{"key":"10.1016\/j.neunet.2026.109137_bib0048","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"21508","article-title":"GeoMVSNet: Learning multi-view stereo with geometry perception","author":"Zhang","year":"2023"},{"key":"10.1016\/j.neunet.2026.109137_bib0049","doi-asserted-by":"crossref","first-page":"502","DOI":"10.1016\/j.neunet.2023.03.012","article-title":"Miper-MVS: Multi-scale iterative probability estimation with refinement for efficient multi-view stereo","volume":"162","author":"Zhou","year":"2023","journal-title":"Neural Networks"}],"container-title":["Neural Networks"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0893608026005988?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0893608026005988?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T15:17:10Z","timestamp":1780067830000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0893608026005988"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,11]]},"references-count":49,"alternative-id":["S0893608026005988"],"URL":"https:\/\/doi.org\/10.1016\/j.neunet.2026.109137","relation":{},"ISSN":["0893-6080"],"issn-type":[{"value":"0893-6080","type":"print"}],"subject":[],"published":{"date-parts":[[2026,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"MGCFI-Net: Multi-scale globally aware feature learning with cross-view feature interaction for multi-view stereo","name":"articletitle","label":"Article Title"},{"value":"Neural Networks","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.neunet.2026.109137","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}],"article-number":"109137"}}