{"title":"AdR-Gaussian:利用自适应半径加速高斯拼接","authors":"Xinzhe Wang, Ran Yi, Lizhuang Ma","doi":"arxiv-2409.08669","DOIUrl":null,"url":null,"abstract":"3D Gaussian Splatting (3DGS) is a recent explicit 3D representation that has\nachieved high-quality reconstruction and real-time rendering of complex scenes.\nHowever, the rasterization pipeline still suffers from unnecessary overhead\nresulting from avoidable serial Gaussian culling, and uneven load due to the\ndistinct number of Gaussian to be rendered across pixels, which hinders wider\npromotion and application of 3DGS. In order to accelerate Gaussian splatting,\nwe propose AdR-Gaussian, which moves part of serial culling in Render stage\ninto the earlier Preprocess stage to enable parallel culling, employing\nadaptive radius to narrow the rendering pixel range for each Gaussian, and\nintroduces a load balancing method to minimize thread waiting time during the\npixel-parallel rendering. Our contributions are threefold, achieving a\nrendering speed of 310% while maintaining equivalent or even better quality\nthan the state-of-the-art. Firstly, we propose to early cull Gaussian-Tile\npairs of low splatting opacity based on an adaptive radius in the\nGaussian-parallel Preprocess stage, which reduces the number of affected tile\nthrough the Gaussian bounding circle, thus reducing unnecessary overhead and\nachieving faster rendering speed. Secondly, we further propose early culling\nbased on axis-aligned bounding box for Gaussian splatting, which achieves a\nmore significant reduction in ineffective expenses by accurately calculating\nthe Gaussian size in the 2D directions. Thirdly, we propose a balancing\nalgorithm for pixel thread load, which compresses the information of heavy-load\npixels to reduce thread waiting time, and enhance information of light-load\npixels to hedge against rendering quality loss. Experiments on three datasets\ndemonstrate that our algorithm can significantly improve the Gaussian Splatting\nrendering speed.","PeriodicalId":501174,"journal":{"name":"arXiv - CS - Graphics","volume":"33 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"AdR-Gaussian: Accelerating Gaussian Splatting with Adaptive Radius\",\"authors\":\"Xinzhe Wang, Ran Yi, Lizhuang Ma\",\"doi\":\"arxiv-2409.08669\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"3D Gaussian Splatting (3DGS) is a recent explicit 3D representation that has\\nachieved high-quality reconstruction and real-time rendering of complex scenes.\\nHowever, the rasterization pipeline still suffers from unnecessary overhead\\nresulting from avoidable serial Gaussian culling, and uneven load due to the\\ndistinct number of Gaussian to be rendered across pixels, which hinders wider\\npromotion and application of 3DGS. In order to accelerate Gaussian splatting,\\nwe propose AdR-Gaussian, which moves part of serial culling in Render stage\\ninto the earlier Preprocess stage to enable parallel culling, employing\\nadaptive radius to narrow the rendering pixel range for each Gaussian, and\\nintroduces a load balancing method to minimize thread waiting time during the\\npixel-parallel rendering. Our contributions are threefold, achieving a\\nrendering speed of 310% while maintaining equivalent or even better quality\\nthan the state-of-the-art. Firstly, we propose to early cull Gaussian-Tile\\npairs of low splatting opacity based on an adaptive radius in the\\nGaussian-parallel Preprocess stage, which reduces the number of affected tile\\nthrough the Gaussian bounding circle, thus reducing unnecessary overhead and\\nachieving faster rendering speed. Secondly, we further propose early culling\\nbased on axis-aligned bounding box for Gaussian splatting, which achieves a\\nmore significant reduction in ineffective expenses by accurately calculating\\nthe Gaussian size in the 2D directions. Thirdly, we propose a balancing\\nalgorithm for pixel thread load, which compresses the information of heavy-load\\npixels to reduce thread waiting time, and enhance information of light-load\\npixels to hedge against rendering quality loss. Experiments on three datasets\\ndemonstrate that our algorithm can significantly improve the Gaussian Splatting\\nrendering speed.\",\"PeriodicalId\":501174,\"journal\":{\"name\":\"arXiv - CS - Graphics\",\"volume\":\"33 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-13\",\"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-2409.08669\",\"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-2409.08669","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
AdR-Gaussian: Accelerating Gaussian Splatting with Adaptive Radius
3D Gaussian Splatting (3DGS) is a recent explicit 3D representation that has
achieved high-quality reconstruction and real-time rendering of complex scenes.
However, the rasterization pipeline still suffers from unnecessary overhead
resulting from avoidable serial Gaussian culling, and uneven load due to the
distinct number of Gaussian to be rendered across pixels, which hinders wider
promotion and application of 3DGS. In order to accelerate Gaussian splatting,
we propose AdR-Gaussian, which moves part of serial culling in Render stage
into the earlier Preprocess stage to enable parallel culling, employing
adaptive radius to narrow the rendering pixel range for each Gaussian, and
introduces a load balancing method to minimize thread waiting time during the
pixel-parallel rendering. Our contributions are threefold, achieving a
rendering speed of 310% while maintaining equivalent or even better quality
than the state-of-the-art. Firstly, we propose to early cull Gaussian-Tile
pairs of low splatting opacity based on an adaptive radius in the
Gaussian-parallel Preprocess stage, which reduces the number of affected tile
through the Gaussian bounding circle, thus reducing unnecessary overhead and
achieving faster rendering speed. Secondly, we further propose early culling
based on axis-aligned bounding box for Gaussian splatting, which achieves a
more significant reduction in ineffective expenses by accurately calculating
the Gaussian size in the 2D directions. Thirdly, we propose a balancing
algorithm for pixel thread load, which compresses the information of heavy-load
pixels to reduce thread waiting time, and enhance information of light-load
pixels to hedge against rendering quality loss. Experiments on three datasets
demonstrate that our algorithm can significantly improve the Gaussian Splatting
rendering speed.