{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T10:11:06Z","timestamp":1784110266194,"version":"3.55.0"},"reference-count":46,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Displays"],"published-print":{"date-parts":[[2026,12]]},"DOI":"10.1016\/j.displa.2026.103614","type":"journal-article","created":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T20:00:56Z","timestamp":1783627256000},"page":"103614","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Geometry-guided explicit\u2013implicit fusion for light field de-occlusion"],"prefix":"10.1016","volume":"95","author":[{"given":"Ruide","family":"Meng","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jieyu","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinpeng","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yilei","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ping","family":"An","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.displa.2026.103614_b1","doi-asserted-by":"crossref","first-page":"20505","DOI":"10.1364\/OE.493686","article-title":"True-color light-field display system with large depth-of-field based on joint modulation for size and arrangement of halftone dots","volume":"31","author":"Yu","year":"2023","journal-title":"Opt. Express"},{"key":"10.1016\/j.displa.2026.103614_b2","doi-asserted-by":"crossref","DOI":"10.1016\/j.displa.2022.102320","article-title":"Virtual stereo content rendering technology review for light-field display","volume":"76","author":"Shen","year":"2023","journal-title":"Displays"},{"issue":"1","key":"10.1016\/j.displa.2026.103614_b3","doi-asserted-by":"crossref","first-page":"24381","DOI":"10.1038\/s41598-024-75172-z","article-title":"Naked-eye light field display technology based on mini\/micro light emitting diode panels: a systematic review and meta-analysis","volume":"14","author":"Wang","year":"2024","journal-title":"Sci. Rep."},{"key":"10.1016\/j.displa.2026.103614_b4","doi-asserted-by":"crossref","DOI":"10.1016\/j.optcom.2024.130458","article-title":"Human gaze prediction for 3D light field display based on multi-attention fusion network","volume":"560","author":"Zhao","year":"2024","journal-title":"Opt. Commun."},{"key":"10.1016\/j.displa.2026.103614_b5","doi-asserted-by":"crossref","DOI":"10.1109\/TIM.2023.3328070","article-title":"Light Field Rectification Based on Relative Pose Estimation","volume":"73","author":"Huo","year":"2024","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"10.1016\/j.displa.2026.103614_b6","doi-asserted-by":"crossref","first-page":"1641","DOI":"10.1109\/TIP.2022.3144891","article-title":"Relative Pose Estimation for Light Field Cameras Based on LF-Point-LF-Point Correspondence Model","volume":"31","author":"Zhang","year":"2022","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.displa.2026.103614_b7","doi-asserted-by":"crossref","first-page":"5493","DOI":"10.1109\/TCE.2024.3436010","article-title":"Prompt Learning for Light Field Semantic Segmentation in the Consumer-Centric Internet of Intelligent Computing Things","volume":"70","author":"Jia","year":"2024","journal-title":"IEEE Trans. Consum. Electron."},{"key":"10.1016\/j.displa.2026.103614_b8","doi-asserted-by":"crossref","unstructured":"J. Luo, X. Jin, M. Liu, Y. Fan, TrafficScene: A Multi-modal Dataset including Light Field for Semantic Segmentation of Traffic Scenes, in: Proceedings of the IEEE International Conference on Multimedia and Expo, ICME, 2024, pp. 1\u20136.","DOI":"10.1109\/ICME57554.2024.10687943"},{"key":"10.1016\/j.displa.2026.103614_b9","doi-asserted-by":"crossref","first-page":"0328","DOI":"10.34133\/research.0328","article-title":"Masked Generative Light Field Prompting for Pixel-Level Structure Segmentations","volume":"7","author":"Wang","year":"2024","journal-title":"Research"},{"key":"10.1016\/j.displa.2026.103614_b10","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1016\/j.neucom.2022.03.056","article-title":"MEANet: Multi-modal edge-aware network for light field salient object detection","volume":"491","author":"Jiang","year":"2022","journal-title":"Neurocomputing"},{"key":"10.1016\/j.displa.2026.103614_b11","doi-asserted-by":"crossref","first-page":"6152","DOI":"10.1109\/TIP.2022.3205749","article-title":"Exploring Spatial Correlation for Light Field Saliency Detection: Expansion From a Single View","volume":"31","author":"Zhang","year":"2022","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.displa.2026.103614_b12","doi-asserted-by":"crossref","DOI":"10.1016\/j.image.2022.116888","article-title":"Fast and accurate light field saliency detection through deep encoding","volume":"110","author":"Hemachandra","year":"2023","journal-title":"Signal Process., Image Commun."},{"key":"10.1016\/j.displa.2026.103614_b13","doi-asserted-by":"crossref","first-page":"6302","DOI":"10.1109\/TIP.2025.3612257","article-title":"Deep Sparse-to-Dense Inbetweening for Multi-View Light Fields","volume":"34","author":"Mao","year":"2025","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.displa.2026.103614_b14","doi-asserted-by":"crossref","unstructured":"Y. Wang, L. Ren, L. Wang, et al., DeOccNet: Learning to see through foreground occlusions in light fields, in: Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020, pp. 2685\u20132693.","DOI":"10.1109\/WACV45572.2020.9093448"},{"key":"10.1016\/j.displa.2026.103614_b15","doi-asserted-by":"crossref","unstructured":"Y. Li, W. Yang, Z. Xu, Z. Chen, Z. Shi, Y. Zhang, L. Huang, Mask4D: 4D convolution network for light field occlusion removal, in: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP, 2021, pp. 2480\u20132484.","DOI":"10.1109\/ICASSP39728.2021.9413449"},{"key":"10.1016\/j.displa.2026.103614_b16","doi-asserted-by":"crossref","unstructured":"S. Zhang, Z. Shen, Y. Lin, Removing foreground occlusions in light field using micro-lens dynamic filter, in: Proceedings of the 30th International Joint Conference on Artificial Intelligence, IJCAI, 2021, pp. 1302\u20131308.","DOI":"10.24963\/ijcai.2021\/180"},{"issue":"10","key":"10.1016\/j.displa.2026.103614_b17","doi-asserted-by":"crossref","first-page":"8012","DOI":"10.1109\/TVCG.2025.3561374","article-title":"Progressive Multi-Plane Images Construction for Light Field Occlusion Removal","volume":"31","author":"Zhang","year":"2025","journal-title":"IEEE Trans. Vis. Comput. Graphics"},{"key":"10.1016\/j.displa.2026.103614_b18","doi-asserted-by":"crossref","unstructured":"V. Vaish, M. Levoy, R. Szeliski, C.L. Zitnick, S.B. Kang, Reconstructing Occluded Surfaces Using Synthetic Apertures: Stereo, Focus and Robust Measures, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2006, pp. 2331\u20132338.","DOI":"10.1109\/CVPR.2006.244"},{"key":"10.1016\/j.displa.2026.103614_b19","doi-asserted-by":"crossref","unstructured":"N. Joshi, S. Avidan, W. Matusik, D.J. Kriegman, Synthetic aperture tracking: Tracking through occlusions, in: Proceedings of the IEEE International Conference on Computer Vision, ICCV, 2007, pp. 1586\u20131593.","DOI":"10.1109\/ICCV.2007.4409032"},{"key":"10.1016\/j.displa.2026.103614_b20","doi-asserted-by":"crossref","first-page":"1461","DOI":"10.1109\/TCSVT.2013.2242553","article-title":"A New Hybrid Synthetic Aperture Imaging Model for Tracking and Seeing People Through Occlusion","volume":"23","author":"Yang","year":"2013","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.displa.2026.103614_b21","doi-asserted-by":"crossref","first-page":"765","DOI":"10.1145\/1073204.1073259","article-title":"High performance imaging using large camera arrays","volume":"24","author":"Wilburn","year":"2005","journal-title":"ACM Trans. Graph."},{"key":"10.1016\/j.displa.2026.103614_b22","doi-asserted-by":"crossref","unstructured":"S. McCloskey, Masking light fields to remove partial occlusion, in: Proceedings of the 22nd International Conference on Pattern Recognition, ICPR, 2014, pp. 2053\u20132058.","DOI":"10.1109\/ICPR.2014.358"},{"key":"10.1016\/j.displa.2026.103614_b23","doi-asserted-by":"crossref","unstructured":"V. Vaish, B. Wilburn, N. Joshi, M. Levoy, Using plane plus disparity for calibrating dense camera arrays, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2004, pp. 2\u20139.","DOI":"10.1109\/CVPR.2004.1315006"},{"key":"10.1016\/j.displa.2026.103614_b24","doi-asserted-by":"crossref","first-page":"2590","DOI":"10.1109\/TCSVT.2022.3226227","article-title":"Effective Light Field De-Occlusion Network Based on Swin Transformer","volume":"33","author":"Wang","year":"2023","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.displa.2026.103614_b25","doi-asserted-by":"crossref","unstructured":"J. Hur, J. Y. Lee, J. Choi, J. Kim, I See-Through You: A Framework for Removing Foreground Occlusion in Both Sparse and Dense Light Field Images, in: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, WACV, 2023, pp. 229\u2013238.","DOI":"10.1109\/WACV56688.2023.00031"},{"key":"10.1016\/j.displa.2026.103614_b26","doi-asserted-by":"crossref","unstructured":"J. Chen, P. An, X. Huang, C. Yang, Adaptive Threshold Mask Prediction and Occlusion-aware Convolution for Foreground Occlusions in Light Fields, in: Proceedings of the IEEE International Conference on Visual Communications and Image Processing, VCIP, 2024, pp. 1\u20135.","DOI":"10.1109\/VCIP63160.2024.10849866"},{"key":"10.1016\/j.displa.2026.103614_b27","series-title":"Computer Vision","first-page":"89","article-title":"Image Inpainting for Irregular Holes Using Partial Convolutions","volume":"vol. 11215","author":"Liu","year":"2018"},{"key":"10.1016\/j.displa.2026.103614_b28","doi-asserted-by":"crossref","unstructured":"J. Li, N. Wang, L. Zhang, B. Du, D. Tao, Recurrent Feature Reasoning for Image Inpainting, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, CVPR, 2020, pp. 7757\u20137765.","DOI":"10.1109\/CVPR42600.2020.00778"},{"key":"10.1016\/j.displa.2026.103614_b29","doi-asserted-by":"crossref","unstructured":"C. Xie, S. Liu, C. Li, M.-M. Cheng, W. Zuo, X. Liu, S. Wen, E. Ding, Image Inpainting with Learnable Bidirectional Attention Maps, in: Proceedings of the IEEE\/CVF International Conference on Computer Vision, ICCV, 2019, pp. 8857\u20138866.","DOI":"10.1109\/ICCV.2019.00895"},{"key":"10.1016\/j.displa.2026.103614_b30","doi-asserted-by":"crossref","first-page":"5027","DOI":"10.1007\/s00371-022-02644-6","article-title":"Light field reconstruction via attention maps of hybrid networks","volume":"39","author":"Liu","year":"2023","journal-title":"Vis. Comput."},{"key":"10.1016\/j.displa.2026.103614_b31","doi-asserted-by":"crossref","first-page":"2839","DOI":"10.1007\/s00371-021-02159-6","article-title":"Depth-guided learning light field angular super-resolution with edge-aware inpainting","volume":"38","author":"Liu","year":"2022","journal-title":"Vis. Comput."},{"key":"10.1016\/j.displa.2026.103614_b32","doi-asserted-by":"crossref","first-page":"425","DOI":"10.1111\/cgf.13849","article-title":"Unsupervised Dense Light Field Reconstruction with Occlusion Awareness","volume":"38","author":"Ni","year":"2019","journal-title":"Comput. Graph. Forum"},{"key":"10.1016\/j.displa.2026.103614_b33","unstructured":"M. Jaderberg, K. Simonyan, A. Zisserman, K. Kavukcuoglu, Spatial Transformer Networks, in: Advances in Neural Information Processing Systems, Vol. 28, NIPS, 2015."},{"key":"10.1016\/j.displa.2026.103614_b34","series-title":"Constructive Theory of Functions of Several Variables","first-page":"85","article-title":"Splines minimizing rotation-invariant semi-norms in Sobolev spaces","author":"Duchon","year":"1977"},{"issue":"8","key":"10.1016\/j.displa.2026.103614_b35","doi-asserted-by":"crossref","first-page":"1602","DOI":"10.3390\/land12081602","article-title":"U-Net-STN: A Novel End-to-End Lake Boundary Prediction Model","volume":"12","author":"Yin","year":"2023","journal-title":"Land"},{"key":"10.1016\/j.displa.2026.103614_b36","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.neucom.2021.04.110","article-title":"STN-enhanced message passing guided by adversarial learning for human pose estimation","volume":"453","author":"Zhou","year":"2021","journal-title":"Neurocomputing"},{"key":"10.1016\/j.displa.2026.103614_b37","series-title":"Computer Vision","first-page":"300","article-title":"SALISA: Saliency-Based Input Sampling for Efficient Video Object Detection","volume":"vol. 13670","author":"Bejnordi","year":"2022"},{"key":"10.1016\/j.displa.2026.103614_b38","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2025.130833","article-title":"Co-speech video generation via motion transfer based on diffusion models","volume":"650","author":"Zhang","year":"2025","journal-title":"Neurocomputing"},{"key":"10.1016\/j.displa.2026.103614_b39","doi-asserted-by":"crossref","unstructured":"K. He, X. Zhang, S. Ren, J. Sun, Deep Residual Learning for Image Recognition, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2016, pp. 770\u2013778.","DOI":"10.1109\/CVPR.2016.90"},{"key":"10.1016\/j.displa.2026.103614_b40","series-title":"The (New) Stanford Light Field Archive","author":"Vaish","year":"2008"},{"key":"10.1016\/j.displa.2026.103614_b41","doi-asserted-by":"crossref","first-page":"600","DOI":"10.1109\/TIP.2003.819861","article-title":"Image quality assessment: From error visibility to structural similarity","volume":"13","author":"Wang","year":"2004","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.displa.2026.103614_b42","series-title":"Adam: A Method for Stochastic Optimization","author":"Kingma","year":"2014"},{"issue":"3","key":"10.1016\/j.displa.2026.103614_b43","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1109\/LSP.2012.2227726","article-title":"Making a \u201cCompletely Blind\u201d Image Quality Analyzer","volume":"20","author":"Mittal","year":"2013","journal-title":"IEEE Signal Process. Lett."},{"issue":"12","key":"10.1016\/j.displa.2026.103614_b44","doi-asserted-by":"crossref","first-page":"4695","DOI":"10.1109\/TIP.2012.2214050","article-title":"No-Reference Image Quality Assessment in the Spatial Domain","volume":"21","author":"Mittal","year":"2012","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.displa.2026.103614_b45","doi-asserted-by":"crossref","unstructured":"L. Yang, B. Kang, Z. Huang, X. Xu, J. Feng, H. Zhao, Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, CVPR, 2024, pp. 10371\u201310381.","DOI":"10.1109\/CVPR52733.2024.00987"},{"issue":"3","key":"10.1016\/j.displa.2026.103614_b46","doi-asserted-by":"crossref","first-page":"1623","DOI":"10.1109\/TPAMI.2020.3019967","article-title":"Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-Shot Cross-Dataset Transfer","volume":"44","author":"Ranftl","year":"2022","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."}],"container-title":["Displays"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0141938226002775?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0141938226002775?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T09:49:27Z","timestamp":1784108967000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0141938226002775"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,12]]},"references-count":46,"alternative-id":["S0141938226002775"],"URL":"https:\/\/doi.org\/10.1016\/j.displa.2026.103614","relation":{},"ISSN":["0141-9382"],"issn-type":[{"value":"0141-9382","type":"print"}],"subject":[],"published":{"date-parts":[[2026,12]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Geometry-guided explicit\u2013implicit fusion for light field de-occlusion","name":"articletitle","label":"Article Title"},{"value":"Displays","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.displa.2026.103614","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"103614"}}