{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T16:09:35Z","timestamp":1777565375898,"version":"3.51.4"},"reference-count":62,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T00:00:00Z","timestamp":1776124800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Computers &amp; Graphics"],"published-print":{"date-parts":[[2026,5]]},"DOI":"10.1016\/j.cag.2026.104593","type":"journal-article","created":{"date-parts":[[2026,4,12]],"date-time":"2026-04-12T17:32:51Z","timestamp":1776015171000},"page":"104593","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"special_numbering":"C","title":["Aniso-GS: Anisotropic appearance field for complex highlight modeling in 3D Gaussian splatting"],"prefix":"10.1016","volume":"136","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5865-5796","authenticated-orcid":false,"given":"Gang","family":"Li","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4797-258X","authenticated-orcid":false,"given":"Zhongliang","family":"Fu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6448-3548","authenticated-orcid":false,"given":"Zhao","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Shengyuan","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"1","key":"10.1016\/j.cag.2026.104593_b1","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"},{"key":"10.1016\/j.cag.2026.104593_b2","series-title":"Proc. IEEE int. conf. comput. vis.","first-page":"5732","article-title":"PlenOctrees for real-time rendering of neural radiance fields","author":"Yu","year":"2021"},{"key":"10.1016\/j.cag.2026.104593_b3","series-title":"Proc. IEEE conf. comput. vis. pattern recognit.","first-page":"16569","article-title":"MobileNeRF: Exploiting the polygon rasterization pipeline for efficient neural field rendering on mobile architectures","author":"Chen","year":"2023"},{"key":"10.1016\/j.cag.2026.104593_b4","series-title":"Proc. euro. conf. comput. vis.","first-page":"333","article-title":"TensoRF: Tensorial radiance fields","author":"Chen","year":"2022"},{"key":"10.1016\/j.cag.2026.104593_b5","series-title":"Proc. IEEE conf. comput. vis. pattern recognit.","first-page":"12479","article-title":"K-Planes: Explicit radiance fields in space, time, and appearance","author":"Fridovich-Keil","year":"2023"},{"key":"10.1016\/j.cag.2026.104593_b6","series-title":"Proc. IEEE int. conf. comput. vis.","first-page":"14315","article-title":"KiloNeRF: Speeding up neural radiance fields with thousands of tiny MLPs","author":"Reiser","year":"2021"},{"issue":"4","key":"10.1016\/j.cag.2026.104593_b7","doi-asserted-by":"crossref","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"},{"issue":"4","key":"10.1016\/j.cag.2026.104593_b8","doi-asserted-by":"crossref","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"},{"issue":"7","key":"10.1016\/j.cag.2026.104593_b9","doi-asserted-by":"crossref","first-page":"6832","DOI":"10.1109\/TCSVT.2025.3538684","article-title":"3D Gaussian splatting: Survey, technologies, challenges, and opportunities","volume":"35","author":"Bao","year":"2025","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"key":"10.1016\/j.cag.2026.104593_b10","series-title":"Proc. adv. neural inf. process. syst. (neurIPS)","article-title":"Spec-Gaussian: Anisotropic view-dependent appearance for 3D Gaussian splatting","author":"Yang","year":"2024"},{"key":"10.1016\/j.cag.2026.104593_b11","doi-asserted-by":"crossref","DOI":"10.1016\/j.cviu.2024.104273","article-title":"Gaussian splatting with NeRF-based color and opacity","volume":"251","author":"Malarz","year":"2025","journal-title":"Comput Vis Image Underst"},{"key":"10.1016\/j.cag.2026.104593_b12","series-title":"Proc. IEEE conf. comput. vis. pattern recognit.","first-page":"5460","article-title":"Mip-NeRF 360: Unbounded anti-aliased neural radiance fields","author":"Barron","year":"2022"},{"key":"10.1016\/j.cag.2026.104593_b13","series-title":"Proc. adv. neural inf. process. syst. (neurIPS)","article-title":"Neural sparse voxel fields","author":"Liu","year":"2020"},{"key":"10.1016\/j.cag.2026.104593_b14","series-title":"Proc. IEEE int. conf. comput. vis.","first-page":"5855","article-title":"Baking neural radiance fields for real-time view synthesis","author":"Hedman","year":"2021"},{"key":"10.1016\/j.cag.2026.104593_b15","series-title":"Proc. IEEE conf. comput. vis. pattern recognit.","first-page":"5491","article-title":"Plenoxels: Radiance fields without neural networks","author":"Fridovich-Keil","year":"2022"},{"key":"10.1016\/j.cag.2026.104593_b16","series-title":"Proc. IEEE conf. comput. vis. pattern recognit.","first-page":"12892","article-title":"EfficientNeRF - efficient neural radiance fields","author":"Hu","year":"2022"},{"key":"10.1016\/j.cag.2026.104593_b17","series-title":"Proc. IEEE conf. comput. vis. pattern recognit.","first-page":"16102","article-title":"Efficient geometry-aware 3D generative adversarial networks","author":"Chan","year":"2022"},{"key":"10.1016\/j.cag.2026.104593_b18","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3592426","article-title":"MERF: Memory-efficient radiance fields for real-time view synthesis in unbounded scenes","volume":"42","author":"Reiser","year":"2023","journal-title":"ACM Trans Graph"},{"key":"10.1016\/j.cag.2026.104593_b19","series-title":"Proc. IEEE conf. comput. vis. pattern recognit.","first-page":"5449","article-title":"Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction","author":"Sun","year":"2022"},{"key":"10.1016\/j.cag.2026.104593_b20","series-title":"Proc. IEEE int. conf. comput. vis.","first-page":"5835","article-title":"Mip-NeRF: A multiscale representation for anti-aliasing neural radiance fields","author":"Barron","year":"2021"},{"key":"10.1016\/j.cag.2026.104593_b21","doi-asserted-by":"crossref","unstructured":"Verbin D, Hedman P, Mildenhall B, Zickler T, Barron JT, Srinivasan PP. Ref-NeRF: Structured View-Dependent Appearance for Neural Radiance Fields. In: Proc. IEEE conf. comput. vis. pattern recognit.. New Orleans, Louisiana, USA; ISBN: 2575-7075, 2022, p. 5481\u201390. http:\/\/dx.doi.org\/10.1109\/CVPR52688.2022.00541.","DOI":"10.1109\/CVPR52688.2022.00541"},{"key":"10.1016\/j.cag.2026.104593_b22","series-title":"Proc. IEEE int. conf. comput. vis.","first-page":"19640","article-title":"Zip-NeRF: Anti-aliased grid-based neural radiance fields","author":"Barron","year":"2023"},{"issue":"4","key":"10.1016\/j.cag.2026.104593_b23","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1111\/cgf.14340","article-title":"DONeRF: Towards real-time rendering of compact neural radiance fields using depth oracle networks","volume":"40","author":"Neff","year":"2021","journal-title":"Comput Graph Forum"},{"key":"10.1016\/j.cag.2026.104593_b24","series-title":"Proc. IEEE conf. comput. vis. pattern recognit.","first-page":"12872","article-title":"Depth-supervised NeRF: Fewer views and faster training for free","author":"Deng","year":"2022"},{"key":"10.1016\/j.cag.2026.104593_b25","series-title":"Proc. IEEE conf. comput. vis. pattern recognit.","first-page":"5428","article-title":"Point-NeRF: Point-based neural radiance fields","author":"Xu","year":"2022"},{"key":"10.1016\/j.cag.2026.104593_b26","series-title":"NeRF++: Analyzing and improving neural radiance fields","author":"Zhang","year":"2020"},{"key":"10.1016\/j.cag.2026.104593_b27","series-title":"Proc. ACM SIGGRAPH","article-title":"Nerfstudio: A modular framework for neural radiance field development","author":"Tancik","year":"2023"},{"key":"10.1016\/j.cag.2026.104593_b28","series-title":"Proc. euro. conf. comput. vis.","first-page":"596","article-title":"Approximate differentiable rendering with algebraic surfaces","author":"Keselman","year":"2022"},{"key":"10.1016\/j.cag.2026.104593_b29","series-title":"Flexible techniques for differentiable rendering with 3D Gaussians","author":"Keselman","year":"2023"},{"issue":"6","key":"10.1016\/j.cag.2026.104593_b30","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3355089.3356513","article-title":"Differentiable surface splatting for point-based geometry processing","volume":"38","author":"Yifan","year":"2019","journal-title":"ACM Trans Graph"},{"key":"10.1016\/j.cag.2026.104593_b31","series-title":"Proc. ACM SIGGRAPH Asia","article-title":"Differentiable point-based radiance fields for efficient view synthesis","author":"Zhang","year":"2022"},{"key":"10.1016\/j.cag.2026.104593_b32","series-title":"Proc. IEEE conf. comput. vis. pattern recognit.","first-page":"4104","article-title":"Structure-from-motion revisited","author":"Sch\u00f6nberger","year":"2016"},{"key":"10.1016\/j.cag.2026.104593_b33","doi-asserted-by":"crossref","unstructured":"Yu Z, Chen A, Huang B, Sattler T, Geiger A. Mip-Splatting: Alias-free 3D Gaussian Splatting. In: Proc. IEEE conf. comput. vis. pattern recognit.. 2024, p. 19447\u201356.","DOI":"10.1109\/CVPR52733.2024.01839"},{"key":"10.1016\/j.cag.2026.104593_b34","series-title":"Proc. IEEE conf. comput. vis. pattern recognit.","first-page":"20654","article-title":"Scaffold-GS: Structured 3D Gaussians for view-adaptive rendering","author":"Lu","year":"2024"},{"key":"10.1016\/j.cag.2026.104593_b35","series-title":"Proc. euro. conf. comput. vis.","first-page":"422","article-title":"HAC: Hash-grid assisted context for 3D Gaussian splatting compression","author":"Chen","year":"2024"},{"key":"10.1016\/j.cag.2026.104593_b36","series-title":"Proc. euro. conf. comput. vis.","first-page":"18","article-title":"Compact 3D scene representation via self-organizing Gaussian grids","author":"Morgenstern","year":"2024"},{"key":"10.1016\/j.cag.2026.104593_b37","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2025.114955","article-title":"FE-GS: 3D feature-embedded Gaussian splatting with geometric regularizations for high-fidelity rendering","volume":"332","author":"Peng","year":"2026","journal-title":"Knowl-Based Syst"},{"key":"10.1016\/j.cag.2026.104593_b38","series-title":"Proc. ACM SIGGRATH","article-title":"2D Gaussian splatting for geometrically accurate radiance fields","author":"Huang","year":"2024"},{"key":"10.1016\/j.cag.2026.104593_b39","doi-asserted-by":"crossref","unstructured":"Gu\u00e9don A, Lepetit V. SuGaR: Surface-Aligned Gaussian Splatting for Efficient 3D Mesh Reconstruction and High-Quality Mesh Rendering. In: Proc. IEEE conf. comput. vis. pattern recognit.. 2024, p. 5354\u201363.","DOI":"10.1109\/CVPR52733.2024.00512"},{"issue":"6","key":"10.1016\/j.cag.2026.104593_b40","article-title":"Gaussian opacity fields: Efficient adaptive surface reconstruction in unbounded scenes","volume":"43","author":"Zehao","year":"2024","journal-title":"ACM Trans Graph"},{"key":"10.1016\/j.cag.2026.104593_b41","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2025.131207","article-title":"NSGHG: Neural surface guided generalizable human Gaussian splatting for sparse view synthesis","volume":"653","author":"Xie","year":"2025","journal-title":"Neurocomputing"},{"key":"10.1016\/j.cag.2026.104593_b42","doi-asserted-by":"crossref","first-page":"11095","DOI":"10.1109\/TMM.2024.3443637","article-title":"GS-SFS: Joint Gaussian splatting and shape-from-silhouette for multiple human reconstruction in large-scale sports scenes","volume":"26","author":"Jiang","year":"2024","journal-title":"IEEE Trans Multimed"},{"key":"10.1016\/j.cag.2026.104593_b43","series-title":"Proc. IEEE conf. comput. vis. pattern recognit.","first-page":"4220","article-title":"SC-gs: Sparse-controlled Gaussian splatting for editable dynamic scenes","author":"Huang","year":"2024"},{"key":"10.1016\/j.cag.2026.104593_b44","series-title":"Proc. IEEE conf. comput. vis. pattern recognit.","first-page":"8508","article-title":"Spacetime Gaussian feature splatting for real-time dynamic view synthesis","author":"Li","year":"2024"},{"key":"10.1016\/j.cag.2026.104593_b45","series-title":"Proc. IEEE conf. comput. vis. pattern recognit.","first-page":"20331","article-title":"Deformable 3D Gaussians for high-fidelity monocular dynamic scene reconstruction","author":"Yang","year":"2024"},{"key":"10.1016\/j.cag.2026.104593_b46","series-title":"Proc. IEEE conf. comput. vis. pattern recognit.","first-page":"4389","article-title":"PhysGaussian: Physics-integrated 3D Gaussians for generative dynamics","author":"Xie","year":"2024"},{"key":"10.1016\/j.cag.2026.104593_b47","doi-asserted-by":"crossref","unstructured":"Wang J, Fang J, Zhang X, Xie L, Tian Q. GaussianEditor: Editing 3D Gaussians Delicately with Text Instructions. In: Proc. IEEE conf. comput. vis. pattern recognit.. 2024, p. 20902\u201311.","DOI":"10.1109\/CVPR52733.2024.01975"},{"key":"10.1016\/j.cag.2026.104593_b48","doi-asserted-by":"crossref","unstructured":"Chen Y, Chen Z, Zhang C, Wang F, Yang X, Wang Y, Cai Z, Yang L, Liu H, Lin G. GaussianEditor: Swift and Controllable 3D Editing with Gaussian Splatting. In: Proc. IEEE conf. comput. vis. pattern recognit.. 2024, p. 21476\u201385.","DOI":"10.1109\/CVPR52733.2024.02029"},{"key":"10.1016\/j.cag.2026.104593_b49","series-title":"Proc. IEEE conf. comput. vis. pattern recognit.","first-page":"6517","article-title":"LucidDreamer: Towards high-fidelity text-to-3D generation via interval score matching","author":"Liang","year":"2024"},{"key":"10.1016\/j.cag.2026.104593_b50","series-title":"Proc. IEEE conf. comput. vis. pattern recognit.","first-page":"21401","article-title":"Text-to-3D using Gaussian splatting","author":"Chen","year":"2024"},{"key":"10.1016\/j.cag.2026.104593_b51","unstructured":"Tang J, Ren J, Zhou H, Liu Z, Zeng G. DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation. In: Int. conf. learn. represent.. 2024."},{"key":"10.1016\/j.cag.2026.104593_b52","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.cag.2026.104593_b53","unstructured":"Fang S, Shen I-C, Igarashi T, Wang Y, Wang Z, Yang Y, Ding W, Zhou S. NeRF Is a Valuable Assistant for 3D Gaussian Splatting. In: Proc. IEEE int. conf. comput. vis.. Honolulu, Hawaii; 2025."},{"key":"10.1016\/j.cag.2026.104593_b54","doi-asserted-by":"crossref","unstructured":"Jiang Y, Tu J, Liu Y, Gao X, Long X, Wang W, Ma Y. GaussianShader: 3D Gaussian Splatting with Shading Functions for Reflective Surfaces. In: Proc. IEEE conf. comput. vis. pattern recognit.. Seattle, Wash., U.S.A.; ISBN: 2575-7075, 2024, p. 5322\u201332. http:\/\/dx.doi.org\/10.1109\/CVPR52733.2024.00509.","DOI":"10.1109\/CVPR52733.2024.00509"},{"key":"10.1016\/j.cag.2026.104593_b55","doi-asserted-by":"crossref","unstructured":"Tang Z, Cham T-J. 3iGS: Factorised Tensorial Illumination for 3D Gaussian Splatting. In: Proc. euro. conf. comput. vis.. 15072, Milan, Italy; 2024, p. 143\u201359. http:\/\/dx.doi.org\/10.1007\/978-3-031-72630-9_9.","DOI":"10.1007\/978-3-031-72630-9_9"},{"key":"10.1016\/j.cag.2026.104593_b56","series-title":"MVGS: Multi-view-regulated Gaussian splatting for novel view synthesis","author":"Du","year":"2024"},{"issue":"9","key":"10.1016\/j.cag.2026.104593_b57","doi-asserted-by":"crossref","first-page":"6100","DOI":"10.1109\/TVCG.2024.3494046","article-title":"PGSR: Planar-based Gaussian splatting for efficient and high-fidelity surface reconstruction","volume":"31","author":"Chen","year":"2025","journal-title":"IEEE Trans Vis Comput Graphics"},{"key":"10.1016\/j.cag.2026.104593_b58","doi-asserted-by":"crossref","unstructured":"Ye Z, Li W, Liu S, Qiao P, Dou Y. AbsGS: Recovering Fine Details in 3D Gaussian Splatting. In: Proc. ACM int. conf. multimed. (ACM MM 24). Melbourne VIC, Australia; 2024, p. 1053\u201361. http:\/\/dx.doi.org\/10.1145\/3664647.3681361.","DOI":"10.1145\/3664647.3681361"},{"key":"10.1016\/j.cag.2026.104593_b59","doi-asserted-by":"crossref","unstructured":"Zhang Z, Hu W, Lao Y, He T, Zhao H. Pixel-GS: Density Control with Pixel-Aware Gradient for 3D Gaussian Splatting. In: Leonardis As, Ricci E, Roth S, Russakovsky O, Sattler T, Varol G, editors. Proc. euro. conf. comput. vis.. Milan, Italy; ISBN: 978-3-031-72655-2, 2024, p. 326\u201342.","DOI":"10.1007\/978-3-031-72655-2_19"},{"key":"10.1016\/j.cag.2026.104593_b60","doi-asserted-by":"crossref","unstructured":"Zadeh A, Chen M, Poria S, Cambria E, Morency L-P. Tensor Fusion Network for Multimodal Sentiment Analysis. In: Proc. conf. empir. methods nat. lang. process., proc.. Copenhagen, Denmark; 2017, p. 1103\u201314. http:\/\/dx.doi.org\/10.18653\/v1\/D17-1115.","DOI":"10.18653\/v1\/D17-1115"},{"issue":"4","key":"10.1016\/j.cag.2026.104593_b61","doi-asserted-by":"crossref","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"},{"issue":"6","key":"10.1016\/j.cag.2026.104593_b62","doi-asserted-by":"crossref","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"}],"container-title":["Computers &amp; Graphics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0097849326000646?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0097849326000646?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T13:24:55Z","timestamp":1776345895000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0097849326000646"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5]]},"references-count":62,"alternative-id":["S0097849326000646"],"URL":"https:\/\/doi.org\/10.1016\/j.cag.2026.104593","relation":{},"ISSN":["0097-8493"],"issn-type":[{"value":"0097-8493","type":"print"}],"subject":[],"published":{"date-parts":[[2026,5]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Aniso-GS: Anisotropic appearance field for complex highlight modeling in 3D Gaussian splatting","name":"articletitle","label":"Article Title"},{"value":"Computers & Graphics","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.cag.2026.104593","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Authors. Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}],"article-number":"104593"}}