{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T00:58:48Z","timestamp":1780880328983,"version":"3.54.1"},"reference-count":45,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100013091","name":"Science and Technology Major Project of Guangxi","doi-asserted-by":"publisher","award":["AA19254016"],"award-info":[{"award-number":["AA19254016"]}],"id":[{"id":"10.13039\/501100013091","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Displays"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1016\/j.displa.2026.103460","type":"journal-article","created":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T01:46:32Z","timestamp":1775180792000},"page":"103460","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Modeling epistemic uncertainty in 3D Gaussian Splatting for robust scene reconstruction"],"prefix":"10.1016","volume":"94","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1743-3139","authenticated-orcid":false,"given":"Qin","family":"Qin","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wang","family":"Qing","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huyuan","family":"Shen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"3","key":"10.1016\/j.displa.2026.103460_b1","doi-asserted-by":"crossref","first-page":"1604","DOI":"10.1109\/TCSVT.2023.3294521","article-title":"Unsupervised single-view synthesis network via style guidance and prior distillation","volume":"34","author":"Liu","year":"2023","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.displa.2026.103460_b2","series-title":"European Conference on Computer Vision","first-page":"265","article-title":"CityGaussian: Real-time high-quality large-scale scene rendering with Gaussians","author":"Liu","year":"2024"},{"key":"10.1016\/j.displa.2026.103460_b3","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2024.129041","article-title":"Monocular thermal SLAM with neural radiance fields for 3D scene reconstruction","volume":"617","author":"Wu","year":"2025","journal-title":"Neurocomputing"},{"issue":"1","key":"10.1016\/j.displa.2026.103460_b4","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1145\/3503250","article-title":"NeRF: Representing scenes as neural radiance fields for view synthesis","volume":"65","author":"Mildenhall","year":"2021","journal-title":"Commun. ACM"},{"issue":"4","key":"10.1016\/j.displa.2026.103460_b5","doi-asserted-by":"crossref","first-page":"139:1","DOI":"10.1145\/3592433","article-title":"3D Gaussian splatting for real-time radiance field rendering","volume":"42","author":"Kerbl","year":"2023","journal-title":"ACM Trans. Graph."},{"key":"10.1016\/j.displa.2026.103460_b6","series-title":"Perceptual-GS: Scene-adaptive perceptual densification for Gaussian splatting","author":"Zhou","year":"2025"},{"key":"10.1016\/j.displa.2026.103460_b7","series-title":"International Conference on Machine Learning","first-page":"1613","article-title":"Weight uncertainty in neural network","author":"Blundell","year":"2015"},{"key":"10.1016\/j.displa.2026.103460_b8","series-title":"Auto-encoding variational bayes","author":"Kingma","year":"2013"},{"key":"10.1016\/j.displa.2026.103460_b9","series-title":"Improving densification in 3D Gaussian splatting for high-fidelity rendering","author":"Deng","year":"2025"},{"key":"10.1016\/j.displa.2026.103460_b10","doi-asserted-by":"crossref","unstructured":"S.S. Mallick, R. Goel, B. Kerbl, M. Steinberger, F.V. Carrasco, F. De La Torre, Taming 3DGS: High-quality radiance fields with limited resources, in: SIGGRAPH Asia 2024 Conference Papers, 2024, pp. 1\u201311.","DOI":"10.1145\/3680528.3687694"},{"key":"10.1016\/j.displa.2026.103460_b11","first-page":"80965","article-title":"3D Gaussian splatting as Markov Chain Monte Carlo","volume":"37","author":"Kheradmand","year":"2024","journal-title":"Adv. Neural Inf. Process. Syst."},{"issue":"2","key":"10.1016\/j.displa.2026.103460_b12","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1109\/2945.468400","article-title":"Optical models for direct volume rendering","volume":"1","author":"Max","year":"2002","journal-title":"IEEE Trans. Vis. Comput. Graphics"},{"key":"10.1016\/j.displa.2026.103460_b13","doi-asserted-by":"crossref","unstructured":"J.T. Barron, B. Mildenhall, M. Tancik, P. Hedman, R. Martin-Brualla, P.P. Srinivasan, Mip-NeRF: A multiscale representation for anti-aliasing neural radiance fields, in: Proceedings of the IEEE\/CVF International Conference on Computer Vision, 2021, pp. 5855\u20135864.","DOI":"10.1109\/ICCV48922.2021.00580"},{"key":"10.1016\/j.displa.2026.103460_b14","doi-asserted-by":"crossref","unstructured":"J.T. Barron, B. Mildenhall, D. Verbin, P.P. Srinivasan, P. Hedman, Mip-NeRF 360: Unbounded anti-aliased neural radiance fields, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2022, pp. 5470\u20135479.","DOI":"10.1109\/CVPR52688.2022.00539"},{"key":"10.1016\/j.displa.2026.103460_b15","doi-asserted-by":"crossref","unstructured":"J.T. Barron, B. Mildenhall, D. Verbin, P.P. Srinivasan, P. Hedman, Zip-NeRF: Anti-aliased grid-based neural radiance fields, in: Proceedings of the IEEE\/CVF International Conference on Computer Vision, 2023, pp. 19697\u201319705.","DOI":"10.1109\/ICCV51070.2023.01804"},{"issue":"4","key":"10.1016\/j.displa.2026.103460_b16","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3528223.3530127","article-title":"Instant neural graphics primitives with a multiresolution hash encoding","volume":"41","author":"M\u00fcller","year":"2022","journal-title":"ACM Trans. Graph."},{"key":"10.1016\/j.displa.2026.103460_b17","doi-asserted-by":"crossref","unstructured":"A. Yu, R. Li, M. Tancik, H. Li, R. Ng, A. Kanazawa, Plenoctrees for real-time rendering of neural radiance fields, in: Proceedings of the IEEE\/CVF International Conference on Computer Vision, 2021, pp. 5752\u20135761.","DOI":"10.1109\/ICCV48922.2021.00570"},{"key":"10.1016\/j.displa.2026.103460_b18","doi-asserted-by":"crossref","unstructured":"G. Wang, Z. Chen, C.C. Loy, Z. Liu, SparseNeRF: Distilling depth ranking for few-shot novel view synthesis, in: Proceedings of the IEEE\/CVF International Conference on Computer Vision, 2023, pp. 9065\u20139076.","DOI":"10.1109\/ICCV51070.2023.00832"},{"key":"10.1016\/j.displa.2026.103460_b19","doi-asserted-by":"crossref","unstructured":"W. Bian, Z. Wang, K. Li, J.-W. Bian, V.A. Prisacariu, Nope-NeRF: Optimising neural radiance field with no pose prior, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2023, pp. 4160\u20134169.","DOI":"10.1109\/CVPR52729.2023.00405"},{"key":"10.1016\/j.displa.2026.103460_b20","doi-asserted-by":"crossref","unstructured":"J. Yang, M. Pavone, Y. Wang, FreeNeRF: Improving few-shot neural rendering with free frequency regularization, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2023, pp. 8254\u20138263.","DOI":"10.1109\/CVPR52729.2023.00798"},{"key":"10.1016\/j.displa.2026.103460_b21","doi-asserted-by":"crossref","unstructured":"A. Pumarola, E. Corona, G. Pons-Moll, F. Moreno-Noguer, D-NeRF: Neural radiance fields for dynamic scenes, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2021, pp. 10318\u201310327.","DOI":"10.1109\/CVPR46437.2021.01018"},{"key":"10.1016\/j.displa.2026.103460_b22","series-title":"HyperNeRF: A higher-dimensional representation for topologically varying neural radiance fields","author":"Park","year":"2021"},{"key":"10.1016\/j.displa.2026.103460_b23","doi-asserted-by":"crossref","unstructured":"G. Wu, T. Yi, J. Fang, L. Xie, X. Zhang, W. Wei, W. Liu, Q. Tian, X. Wang, 4d Gaussian splatting for real-time dynamic scene rendering, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2024, pp. 20310\u201320320.","DOI":"10.1109\/CVPR52733.2024.01920"},{"key":"10.1016\/j.displa.2026.103460_b24","doi-asserted-by":"crossref","unstructured":"E. Sandstr\u00f6m, G. Zhang, K. Tateno, M. Oechsle, M. Niemeyer, Y. Zhang, M. Patel, L. Van Gool, M. Oswald, F. Tombari, Splat-SLAM: Globally optimized RGB-only SLAM with 3D Gaussians, in: Proceedings of the Computer Vision and Pattern Recognition Conference, 2025, pp. 1680\u20131691.","DOI":"10.1109\/CVPRW67362.2025.00156"},{"key":"10.1016\/j.displa.2026.103460_b25","doi-asserted-by":"crossref","unstructured":"C. Yan, D. Qu, D. Xu, B. Zhao, Z. Wang, D. Wang, X. Li, Gs-SLAM: Dense visual SLAM with 3D Gaussian splatting, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2024, pp. 19595\u201319604.","DOI":"10.1109\/CVPR52733.2024.01853"},{"key":"10.1016\/j.displa.2026.103460_b26","doi-asserted-by":"crossref","unstructured":"H. Matsuki, R. Murai, P.H. Kelly, A.J. Davison, Gaussian splatting SLAM, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2024, pp. 18039\u201318048.","DOI":"10.1109\/CVPR52733.2024.01708"},{"key":"10.1016\/j.displa.2026.103460_b27","series-title":"GP-GS: Gaussian processes for enhanced Gaussian splatting","author":"Guo","year":"2025"},{"key":"10.1016\/j.displa.2026.103460_b28","series-title":"Citygaussianv2: Efficient and geometrically accurate reconstruction for large-scale scenes","author":"Liu","year":"2024"},{"key":"10.1016\/j.displa.2026.103460_b29","series-title":"ScalingGaussian: Enhancing 3D content creation with generative Gaussian splatting","author":"Chen","year":"2024"},{"key":"10.1016\/j.displa.2026.103460_b30","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2025.130475","article-title":"Talent3D: Optimizing geometry and enhancing appearance for high-quality Text-to-3D shape generation","volume":"645","author":"Wang","year":"2025","journal-title":"Neurocomputing"},{"key":"10.1016\/j.displa.2026.103460_b31","series-title":"Furniscene: A large-scale 3D room dataset with intricate furnishing scenes","author":"Zhang","year":"2024"},{"key":"10.1016\/j.displa.2026.103460_b32","series-title":"Cityx: Controllable procedural content generation for unbounded 3D cities","author":"Zhang","year":"2024"},{"key":"10.1016\/j.displa.2026.103460_b33","doi-asserted-by":"crossref","unstructured":"Z. Li, Z. Zheng, L. Wang, Y. Liu, Animatable gaussians: Learning pose-dependent Gaussian maps for high-fidelity human avatar modeling, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2024, pp. 19711\u201319722.","DOI":"10.1109\/CVPR52733.2024.01864"},{"key":"10.1016\/j.displa.2026.103460_b34","series-title":"European Conference on Computer Vision","first-page":"326","article-title":"Pixel-gs: Density control with pixel-aware gradient for 3D Gaussian splatting","author":"Zhang","year":"2024"},{"key":"10.1016\/j.displa.2026.103460_b35","series-title":"European Conference on Computer Vision","first-page":"347","article-title":"Revising densification in Gaussian splatting","author":"Rota Bul\u00f2","year":"2024"},{"key":"10.1016\/j.displa.2026.103460_b36","doi-asserted-by":"crossref","unstructured":"Z. Ye, W. Li, S. Liu, P. Qiao, Y. Dou, AbsGS: Recovering fine details in 3D Gaussian splatting, in: Proceedings of the 32nd ACM International Conference on Multimedia, 2024, pp. 1053\u20131061.","DOI":"10.1145\/3664647.3681361"},{"key":"10.1016\/j.displa.2026.103460_b37","unstructured":"X. Deng, Q. Yu, C. Diao, M. Li, D. Xu, Gradient-Driven Natural Selection for Compact 3D Gaussian Splatting, 2025, arXiv preprint arXiv:2511.16980."},{"key":"10.1016\/j.displa.2026.103460_b38","unstructured":"T. Van de Maele, O. \u00c7atal, A. Tschantz, C.L. Buckley, T. Verbelen, Variational Bayes Gaussian Splatting, 2024, arXiv preprint arXiv:2410.03592."},{"key":"10.1016\/j.displa.2026.103460_b39","first-page":"87934","article-title":"Variational multi-scale representation for estimating uncertainty in 3D Gaussian splatting","volume":"37","author":"Li","year":"2024","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.displa.2026.103460_b40","article-title":"What uncertainties do we need in bayesian deep learning for computer vision?","volume":"30","author":"Kendall","year":"2017","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.displa.2026.103460_b41","article-title":"UC-NeRF: Uncertainty-aware conditional neural radiance fields from endoscopic sparse views","author":"Guo","year":"2024","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.displa.2026.103460_b42","series-title":"ProbNVS: Fast novel view synthesis with learned probability-guided sampling","author":"Zhou","year":"2022"},{"issue":"4","key":"10.1016\/j.displa.2026.103460_b43","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 Trans. Graph. (ToG)"},{"issue":"6","key":"10.1016\/j.displa.2026.103460_b44","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3272127.3275084","article-title":"Deep blending for free-viewpoint image-based rendering","volume":"37","author":"Hedman","year":"2018","journal-title":"ACM Trans. Graph. (ToG)"},{"key":"10.1016\/j.displa.2026.103460_b45","doi-asserted-by":"crossref","unstructured":"R. Zhang, P. Isola, A.A. Efros, E. Shechtman, O. Wang, The unreasonable effectiveness of deep features as a perceptual metric, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018, pp. 586\u2013595.","DOI":"10.1109\/CVPR.2018.00068"}],"container-title":["Displays"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S014193822600123X?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S014193822600123X?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T00:12:21Z","timestamp":1780877541000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S014193822600123X"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":45,"alternative-id":["S014193822600123X"],"URL":"https:\/\/doi.org\/10.1016\/j.displa.2026.103460","relation":{},"ISSN":["0141-9382"],"issn-type":[{"value":"0141-9382","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Modeling epistemic uncertainty in 3D Gaussian Splatting for robust scene reconstruction","name":"articletitle","label":"Article Title"},{"value":"Displays","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.displa.2026.103460","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":"103460"}}