Mip-Splatting: Alias-Free 3D Gaussian Splatting

Zehao Yu, Anpei Chen, Binbin Huang, Torsten Sattler, Andreas Geiger
2/14/2026

No official code found. Best implementation: autonomousvision/mip-splatting (1,477 stars, last commit 2024-12-17).

Abstract

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, e.g., 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 to constrains the size of the 3D Gaussian primitives based on the maximal sampling frequency induced by the input views. It eliminates 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.

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Code Implementations(1)

[CVPR'24 Best Student Paper] Mip-Splatting: Alias-free 3D Gaussian Splatting

1,477121C, C++Nov 27, 20231 years agoNOASSERTION
3d-reconstructionanti-aliasingguassian-splattingnerfnovel-view-synthesis

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Cite this paper

@article{yu2026mipsplatting,
  title  = {Mip-Splatting: Alias-Free 3D Gaussian Splatting},
  author = {Zehao Yu and Anpei Chen and Binbin Huang and Torsten Sattler and Andreas Geiger},
  year   = {2026},
  eprint = {2311.16493},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/pdf/2311.16493},
  journal = {CVPR 2023 2023}
}

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