Mip-Splatting: Alias-free 3D Gaussian Splatting
2023-11-27
会议录名称ARXIV
ISSN1063-6919
发表状态已发表
DOIarXiv:2311.16493
摘要

Recently, 3D Gaussian Splatting has demonstrated impressive novel view synthesis results, reaching high fidelity and efficiency. However, strong artifacts can be observed when changing the sampling rate, eg, by changing focal length or camera distance. We find that the source for this phenomenon can be attributed to the lack of 3D frequency constraints and the usage of a 2D dilation filter. To address this problem, we introduce a 3D smoothing filter which constrains the size of the 3D Gaussian primitives based on the maximal sampling frequency induced by the input views, eliminating high-frequency artifacts when zooming in. Moreover, replacing 2D dilation with a 2D Mip filter, which simulates a 2D box filter, effectively mitigates aliasing and dilation issues. Our evaluation, including scenarios such a training on single-scale images and testing on multiple scales, validates the effectiveness of our approach.

会议地点Seattle, WA, USA
会议日期16-22 June 2024
URL查看原文
WOS类目Computer Science, Software Engineering
WOS记录号PPRN:86311595
来源库IEEE
文献类型会议论文
条目标识符https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/381367
专题信息科学与技术学院_博士生
通讯作者Yu, Zehao
作者单位
1.Univ Tubingen, Tubingen, Germany
2.Tubingen AI Ctr, Tubingen, Germany
3.ShanghaiTech Univ, Shanghai, Peoples R China
4.Czech Tech Univ Prague, Prague, Czech Republic
推荐引用方式
GB/T 7714
Yu, Zehao,Chen, Anpei,Huang, Binbin,et al. Mip-Splatting: Alias-free 3D Gaussian Splatting[C],2023.
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