  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.

Computer Vision and Pattern Recognition