A survey on surface reconstruction based on 3D Gaussian splatting
Surface reconstruction is a foundational topic in computer graphics and has gained substantial research interest in recent years. With the emergence of advanced neural radiance fields (NeRFs) and 3D Gaussian splatting (3D GS), numerous innovative many novel algorithms for 3D model surface reconstruc...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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PeerJ Inc.
2025-08-01
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| Series: | PeerJ Computer Science |
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| Online Access: | https://peerj.com/articles/cs-3034.pdf |
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| _version_ | 1849391639744741376 |
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| author | Zheng Xu Gang Chen Feng Li Lingyu Chen Yuanhang Cheng |
| author_facet | Zheng Xu Gang Chen Feng Li Lingyu Chen Yuanhang Cheng |
| author_sort | Zheng Xu |
| collection | DOAJ |
| description | Surface reconstruction is a foundational topic in computer graphics and has gained substantial research interest in recent years. With the emergence of advanced neural radiance fields (NeRFs) and 3D Gaussian splatting (3D GS), numerous innovative many novel algorithms for 3D model surface reconstruction have been developed. The rapid expansion of this field presents challenges in tracking ongoing advancements. This survey aims to present core methodologies for the surface reconstruction of 3D models and establish a structured roadmap that encompasses 3D representations, reconstruction methods, datasets, and related applications. Specifically, we introduce 3D representations using 3D Gaussians as the central framework. Additionally, we provide a comprehensive overview of the rapidly evolving surface reconstruction methods based on 3D Gaussian splatting. We categorize the primary phases of surface reconstruction algorithms for 3D models into scene representation, Gaussian optimization, and surface structure extraction. Finally, we review the available datasets, applications, and challenges and suggest potential future research directions in this domain. Through this survey, we aim to provide valuable resources that support and inspire researchers in the field, fostering advancements in 3D reconstruction technologies. |
| format | Article |
| id | doaj-art-9a3c60285f8c4b37a4df32a0d7f7f0c4 |
| institution | Kabale University |
| issn | 2376-5992 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | PeerJ Inc. |
| record_format | Article |
| series | PeerJ Computer Science |
| spelling | doaj-art-9a3c60285f8c4b37a4df32a0d7f7f0c42025-08-20T03:41:00ZengPeerJ Inc.PeerJ Computer Science2376-59922025-08-0111e303410.7717/peerj-cs.3034A survey on surface reconstruction based on 3D Gaussian splattingZheng XuGang ChenFeng LiLingyu ChenYuanhang ChengSurface reconstruction is a foundational topic in computer graphics and has gained substantial research interest in recent years. With the emergence of advanced neural radiance fields (NeRFs) and 3D Gaussian splatting (3D GS), numerous innovative many novel algorithms for 3D model surface reconstruction have been developed. The rapid expansion of this field presents challenges in tracking ongoing advancements. This survey aims to present core methodologies for the surface reconstruction of 3D models and establish a structured roadmap that encompasses 3D representations, reconstruction methods, datasets, and related applications. Specifically, we introduce 3D representations using 3D Gaussians as the central framework. Additionally, we provide a comprehensive overview of the rapidly evolving surface reconstruction methods based on 3D Gaussian splatting. We categorize the primary phases of surface reconstruction algorithms for 3D models into scene representation, Gaussian optimization, and surface structure extraction. Finally, we review the available datasets, applications, and challenges and suggest potential future research directions in this domain. Through this survey, we aim to provide valuable resources that support and inspire researchers in the field, fostering advancements in 3D reconstruction technologies.https://peerj.com/articles/cs-3034.pdf3D reconstruction3D Gaussian splattingSurface reconstructionMulti-view imagery |
| spellingShingle | Zheng Xu Gang Chen Feng Li Lingyu Chen Yuanhang Cheng A survey on surface reconstruction based on 3D Gaussian splatting PeerJ Computer Science 3D reconstruction 3D Gaussian splatting Surface reconstruction Multi-view imagery |
| title | A survey on surface reconstruction based on 3D Gaussian splatting |
| title_full | A survey on surface reconstruction based on 3D Gaussian splatting |
| title_fullStr | A survey on surface reconstruction based on 3D Gaussian splatting |
| title_full_unstemmed | A survey on surface reconstruction based on 3D Gaussian splatting |
| title_short | A survey on surface reconstruction based on 3D Gaussian splatting |
| title_sort | survey on surface reconstruction based on 3d gaussian splatting |
| topic | 3D reconstruction 3D Gaussian splatting Surface reconstruction Multi-view imagery |
| url | https://peerj.com/articles/cs-3034.pdf |
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