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Mip-Splatting: Alias-free 3D Gaussian Splatting

About

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.

Zehao Yu, Anpei Chen, Binbin Huang, Torsten Sattler, Andreas Geiger• 2023

Related benchmarks

TaskDatasetResultRank
Novel View SynthesisMip-NeRF 360 (test)
PSNR27.79
166
Novel View SynthesisMipNeRF 360 Outdoor
PSNR24.65
112
Novel View SynthesisMipNeRF 360 Indoor
PSNR30.9
108
Novel View SynthesisMip-NeRF360
PSNR27.79
104
Novel View SynthesisNeRF Synthetic
PSNR33.92
92
Novel View SynthesisSynthetic-NeRF (test)
PSNR27.507
48
Novel View SynthesisBlender (test)
PSNR31.97
37
3D ReconstructionTanks&Temples
PSNR20.08
22
Novel View SynthesisDeep Blending
PSNR29.69
21
3D ReconstructionDL3DV-140
PSNR26.29
18
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