{"title":"2DGH:二维高斯-赫米特拼接技术实现高质量渲染和更好的几何重构","authors":"Ruihan Yu, Tianyu Huang, Jingwang Ling, Feng Xu","doi":"arxiv-2408.16982","DOIUrl":null,"url":null,"abstract":"2D Gaussian Splatting has recently emerged as a significant method in 3D\nreconstruction, enabling novel view synthesis and geometry reconstruction\nsimultaneously. While the well-known Gaussian kernel is broadly used, its lack\nof anisotropy and deformation ability leads to dim and vague edges at object\nsilhouettes, limiting the reconstruction quality of current Gaussian splatting\nmethods. To enhance the representation power, we draw inspiration from quantum\nphysics and propose to use the Gaussian-Hermite kernel as the new primitive in\nGaussian splatting. The new kernel takes a unified mathematical form and\nextends the Gaussian function, which serves as the zero-rank term in the\nupdated formulation. Our experiments demonstrate the extraordinary performance\nof Gaussian-Hermite kernel in both geometry reconstruction and novel-view\nsynthesis tasks. The proposed kernel outperforms traditional Gaussian Splatting\nkernels, showcasing its potential for high-quality 3D reconstruction and\nrendering.","PeriodicalId":501174,"journal":{"name":"arXiv - CS - Graphics","volume":"181 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"2DGH: 2D Gaussian-Hermite Splatting for High-quality Rendering and Better Geometry Reconstruction\",\"authors\":\"Ruihan Yu, Tianyu Huang, Jingwang Ling, Feng Xu\",\"doi\":\"arxiv-2408.16982\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"2D Gaussian Splatting has recently emerged as a significant method in 3D\\nreconstruction, enabling novel view synthesis and geometry reconstruction\\nsimultaneously. While the well-known Gaussian kernel is broadly used, its lack\\nof anisotropy and deformation ability leads to dim and vague edges at object\\nsilhouettes, limiting the reconstruction quality of current Gaussian splatting\\nmethods. To enhance the representation power, we draw inspiration from quantum\\nphysics and propose to use the Gaussian-Hermite kernel as the new primitive in\\nGaussian splatting. The new kernel takes a unified mathematical form and\\nextends the Gaussian function, which serves as the zero-rank term in the\\nupdated formulation. Our experiments demonstrate the extraordinary performance\\nof Gaussian-Hermite kernel in both geometry reconstruction and novel-view\\nsynthesis tasks. The proposed kernel outperforms traditional Gaussian Splatting\\nkernels, showcasing its potential for high-quality 3D reconstruction and\\nrendering.\",\"PeriodicalId\":501174,\"journal\":{\"name\":\"arXiv - CS - Graphics\",\"volume\":\"181 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-08-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - CS - Graphics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2408.16982\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Graphics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2408.16982","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
2DGH: 2D Gaussian-Hermite Splatting for High-quality Rendering and Better Geometry Reconstruction
2D Gaussian Splatting has recently emerged as a significant method in 3D
reconstruction, enabling novel view synthesis and geometry reconstruction
simultaneously. While the well-known Gaussian kernel is broadly used, its lack
of anisotropy and deformation ability leads to dim and vague edges at object
silhouettes, limiting the reconstruction quality of current Gaussian splatting
methods. To enhance the representation power, we draw inspiration from quantum
physics and propose to use the Gaussian-Hermite kernel as the new primitive in
Gaussian splatting. The new kernel takes a unified mathematical form and
extends the Gaussian function, which serves as the zero-rank term in the
updated formulation. Our experiments demonstrate the extraordinary performance
of Gaussian-Hermite kernel in both geometry reconstruction and novel-view
synthesis tasks. The proposed kernel outperforms traditional Gaussian Splatting
kernels, showcasing its potential for high-quality 3D reconstruction and
rendering.