{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,22]],"date-time":"2026-06-22T13:52:09Z","timestamp":1782136329848,"version":"3.54.5"},"reference-count":48,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"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":["Computers & Graphics"],"published-print":{"date-parts":[[2026,6]]},"DOI":"10.1016\/j.cag.2026.104622","type":"journal-article","created":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T15:26:36Z","timestamp":1778167596000},"page":"104622","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"special_numbering":"C","title":["Efficient large-scale 3D Gaussian splatting reconstruction via scene-aware subscene training"],"prefix":"10.1016","volume":"137","author":[{"given":"Yanping","family":"Zhu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sen","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chengjin","family":"Hong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenhao","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"8","key":"10.1016\/j.cag.2026.104622_b1","doi-asserted-by":"crossref","first-page":"4515","DOI":"10.1177\/14614448251336434","article-title":"Digital twins as planetary media in Europe and China: Optimization and resilience in scientific and socioeconomic domains","volume":"27","author":"Kim","year":"2025","journal-title":"New Media Soc"},{"key":"10.1016\/j.cag.2026.104622_b2","doi-asserted-by":"crossref","DOI":"10.1177\/27541258251316856","article-title":"Groundtruthing the digital twin","author":"Halegoua","year":"2025","journal-title":"Dialogues Urban Res"},{"key":"10.1016\/j.cag.2026.104622_b3","series-title":"European conference on computer vision","first-page":"156","article-title":"Street Gaussians: Modeling dynamic urban scenes with Gaussian splatting","author":"Yan","year":"2024"},{"key":"10.1016\/j.cag.2026.104622_b4","first-page":"1","article-title":"S-NeRF++: Autonomous driving simulation via neural reconstruction and generation","author":"Chen","year":"2025","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"10.1016\/j.cag.2026.104622_b5","series-title":"2019 IEEE conference on virtual reality and 3D user interfaces","first-page":"1030","article-title":"Novel view synthesis with multiple 360 images for large-scale 6-DOF virtual reality system","author":"Cho","year":"2019"},{"key":"10.1016\/j.cag.2026.104622_b6","first-page":"1","article-title":"Can I get there? Negotiated user-to-user teleportations in social VR","author":"Wang","year":"2025","journal-title":"IEEE Trans Vis Comput Graphics"},{"key":"10.1016\/j.cag.2026.104622_b7","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"12922","article-title":"Mega-NeRF: Scalable construction of large-scale NeRFs for virtual fly-throughs","author":"Turki","year":"2022"},{"issue":"3","key":"10.1016\/j.cag.2026.104622_b8","doi-asserted-by":"crossref","first-page":"835","DOI":"10.1145\/1141911.1141964","article-title":"Photo tourism: Exploring photo collections in 3D","volume":"25","author":"Snavely","year":"2006","journal-title":"ACM Trans Graph"},{"key":"10.1016\/j.cag.2026.104622_b9","series-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","first-page":"1430","article-title":"Towards high-resolution large-scale multi-view stereo","author":"Vu","year":"2009"},{"issue":"3","key":"10.1016\/j.cag.2026.104622_b10","doi-asserted-by":"crossref","first-page":"29:1","DOI":"10.1145\/2487228.2487237","article-title":"Screened Poisson surface reconstruction","volume":"32","author":"Kazhdan","year":"2013","journal-title":"ACM Trans Graph"},{"issue":"1","key":"10.1016\/j.cag.2026.104622_b11","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1561\/2300000035","article-title":"A review of point cloud registration algorithms for mobile robotics","volume":"4","author":"Pomerleau","year":"2015","journal-title":"Found Trends Robot"},{"key":"10.1016\/j.cag.2026.104622_b12","doi-asserted-by":"crossref","DOI":"10.3389\/fphy.2021.817102","article-title":"3D reconstruction of non-lambertian surfaces by perspective shape-from-shading with fast viscosity solution","volume":"9","author":"Wang","year":"2022","journal-title":"Front Phys"},{"issue":"1","key":"10.1016\/j.cag.2026.104622_b13","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.cag.2026.104622_b14","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.cag.2026.104622_b15","series-title":"Proceedings of the 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"},{"issue":"10","key":"10.1016\/j.cag.2026.104622_b16","doi-asserted-by":"crossref","first-page":"2423","DOI":"10.1109\/TPAMI.2019.2929170","article-title":"Confidence propagation through cnns for guided sparse depth regression","volume":"42","author":"Eldesokey","year":"2019","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"10.1016\/j.cag.2026.104622_b17","series-title":"2019 16th international conference on machine vision applications","first-page":"1","article-title":"Sparse and noisy lidar completion with rgb guidance and uncertainty","author":"Van Gansbeke","year":"2019"},{"key":"10.1016\/j.cag.2026.104622_b18","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"5166","article-title":"VastGaussian: Vast 3D Gaussians for large scene reconstruction","author":"Lin","year":"2024"},{"key":"10.1016\/j.cag.2026.104622_b19","series-title":"BlockGaussian: Efficient large-scale scene novel view synthesis via adaptive block-based Gaussian splatting","author":"Wu","year":"2025"},{"key":"10.1016\/j.cag.2026.104622_b20","doi-asserted-by":"crossref","unstructured":"Li L, Shen Z, Wang Z, Shen L, Bo L. Compressing Volumetric Radiance Fields to 1 MB. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition. 2023, p. 4222\u201331.","DOI":"10.1109\/CVPR52729.2023.00411"},{"key":"10.1016\/j.cag.2026.104622_b21","doi-asserted-by":"crossref","unstructured":"Fridovich-Keil S, Yu A, Tancik M, Chen Q, Recht B, Kanazawa A. Plenoxels: Radiance Fields Without Neural Networks. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition. 2022, p. 5501\u201310.","DOI":"10.1109\/CVPR52688.2022.00542"},{"key":"10.1016\/j.cag.2026.104622_b22","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"21719","article-title":"Compact 3D Gaussian representation for radiance field","author":"Lee","year":"2024"},{"key":"10.1016\/j.cag.2026.104622_b23","doi-asserted-by":"crossref","first-page":"140138","DOI":"10.52202\/079017-4447","article-title":"LightGaussian: Unbounded 3D Gaussian compression with 15\u00d7 reduction and 200+ FPS","volume":"37","author":"Fan","year":"2024","journal-title":"Adv Neural Inf Process Syst"},{"key":"10.1016\/j.cag.2026.104622_b24","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"8248","article-title":"Block-NeRF: Scalable large scene neural view synthesis","author":"Tancik","year":"2022"},{"key":"10.1016\/j.cag.2026.104622_b25","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"7210","article-title":"NeRF in the wild: Neural radiance fields for unconstrained photo collections","author":"Martin-Brualla","year":"2021"},{"key":"10.1016\/j.cag.2026.104622_b26","series-title":"Proceedings of the eleventh international conference on learning representations","article-title":"Switch-NeRF: Learning scene decomposition with mixture of experts for large-scale neural radiance fields","author":"Mi","year":"2022"},{"key":"10.1016\/j.cag.2026.104622_b27","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"8296","article-title":"Grid-guided neural radiance fields for large urban scenes","author":"Xu","year":"2023"},{"key":"10.1016\/j.cag.2026.104622_b28","doi-asserted-by":"crossref","first-page":"34487","DOI":"10.52202\/079017-1087","article-title":"DOGS: Distributed-oriented Gaussian splatting for large-scale 3D reconstruction via Gaussian consensus","volume":"37","author":"Chen","year":"2024","journal-title":"Adv Neural Inf Process Syst"},{"key":"10.1016\/j.cag.2026.104622_b29","series-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","first-page":"652","article-title":"PointNet: Deep learning on point sets for 3D classification and segmentation","author":"Qi","year":"2017"},{"key":"10.1016\/j.cag.2026.104622_b30","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"11108","article-title":"RandLA-Net: Efficient semantic segmentation of large-scale point clouds","author":"Hu","year":"2020"},{"issue":"3","key":"10.1016\/j.cag.2026.104622_b31","doi-asserted-by":"crossref","first-page":"666","DOI":"10.1109\/TSP.2017.2771730","article-title":"Fast resampling of three-dimensional point clouds via graphs","volume":"66","author":"Chen","year":"2017","journal-title":"IEEE Trans Signal Process"},{"key":"10.1016\/j.cag.2026.104622_b32","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"7578","article-title":"SampleNet: Differentiable point cloud sampling","author":"Lang","year":"2020"},{"issue":"3","key":"10.1016\/j.cag.2026.104622_b33","first-page":"3274","article-title":"Intrinsic and isotropic resampling for 3D point clouds","volume":"45","author":"Lv","year":"2023","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"10.1016\/j.cag.2026.104622_b34","unstructured":"Moenning C, Dodgson NA. Intrinsic Point Cloud Simplification. In: Proceedings of the 14th international conference in central europe on computer graphics, visualization and computer vision. 2004, p. 1\u20138."},{"key":"10.1016\/j.cag.2026.104622_b35","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"17671","article-title":"Learnable skeleton-aware 3D point cloud sampling","author":"Wen","year":"2023"},{"key":"10.1016\/j.cag.2026.104622_b36","series-title":"Proceedings of the IEEE\/CVF winter conference on applications of computer vision","first-page":"1236","article-title":"Compressing explicit voxel grid representations: Fast NeRFs become also small","author":"Deng","year":"2023"},{"key":"10.1016\/j.cag.2026.104622_b37","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"20680","article-title":"Masked wavelet representation for compact neural radiance fields","author":"Rho","year":"2023"},{"key":"10.1016\/j.cag.2026.104622_b38","series-title":"Proceedings of the IEEE\/CVF international conference on computer vision","first-page":"3480","article-title":"HollowNeRF: Pruning HashGrid-based NeRFs with trainable collision mitigation","author":"Xie","year":"2023"},{"key":"10.1016\/j.cag.2026.104622_b39","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"10349","article-title":"Compressed 3D Gaussian splatting for accelerated novel view synthesis","author":"Niedermayr","year":"2024"},{"key":"10.1016\/j.cag.2026.104622_b40","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"10371","article-title":"Depth anything: Unleashing the power of large-scale unlabeled data","author":"Yang","year":"2024"},{"key":"10.1016\/j.cag.2026.104622_b41","first-page":"845","article-title":"The manhattan world assumption: Regularities in scene statistics which enable Bayesian inference","volume":"vol. 13","author":"Coughlan","year":"2001"},{"key":"10.1016\/j.cag.2026.104622_b42","doi-asserted-by":"crossref","unstructured":"Lin L, Liu Y, Hu Y, Yan X, Xie K, Huang H. Capturing, Reconstructing, and Simulating: The UrbanScene3D Dataset. In: European conference on computer vision. 2022, p. 93\u2013109.","DOI":"10.1007\/978-3-031-20074-8_6"},{"key":"10.1016\/j.cag.2026.104622_b43","doi-asserted-by":"crossref","unstructured":"Zhang R, Isola P, Efros AA, Shechtman E, Wang O. The Unreasonable Effectiveness of Deep Features as a Perceptual Metric. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition. 2018, p. 586\u201395.","DOI":"10.1109\/CVPR.2018.00068"},{"issue":"1","key":"10.1016\/j.cag.2026.104622_b44","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3651282","article-title":"Reducing the memory footprint of 3D Gaussian splatting","volume":"7","author":"Papantonakis","year":"2024","journal-title":"Proc ACM Comput Graph Interact Tech"},{"key":"10.1016\/j.cag.2026.104622_b45","series-title":"Computer vision \u2013 ECCV 2024","first-page":"165","article-title":"Mini-splatting: Representing scenes with a constrained number of Gaussians","volume":"vol. 15086","author":"Fang","year":"2024"},{"issue":"4","key":"10.1016\/j.cag.2026.104622_b46","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)"},{"key":"10.1016\/j.cag.2026.104622_b47","doi-asserted-by":"crossref","unstructured":"Barron JT, Mildenhall B, Verbin D, Srinivasan PP, Hedman P. Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fields. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition. 2022, p. 5470\u20139.","DOI":"10.1109\/CVPR52688.2022.00539"},{"key":"10.1016\/j.cag.2026.104622_b48","doi-asserted-by":"crossref","unstructured":"Li Y, Jiang L, Xu L, Xiangli Y, Wang Z, Lin D, Dai B. Matrixcity: A large-scale city dataset for city-scale neural rendering and beyond. In: Proceedings of the IEEE\/CVF international conference on computer vision. 2023, p. 3205\u201315.","DOI":"10.1109\/ICCV51070.2023.00297"}],"container-title":["Computers & Graphics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0097849326000932?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0097849326000932?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,22]],"date-time":"2026-06-22T13:12:13Z","timestamp":1782133933000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0097849326000932"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6]]},"references-count":48,"alternative-id":["S0097849326000932"],"URL":"https:\/\/doi.org\/10.1016\/j.cag.2026.104622","relation":{},"ISSN":["0097-8493"],"issn-type":[{"value":"0097-8493","type":"print"}],"subject":[],"published":{"date-parts":[[2026,6]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Efficient large-scale 3D Gaussian splatting reconstruction via scene-aware subscene training","name":"articletitle","label":"Article Title"},{"value":"Computers & Graphics","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.cag.2026.104622","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":"104622"}}