Misalignment of generated gaussian with initial point cloud

[MotivaCG]

When generating the Gaussian in GSplat, I observed a misalignment with the initial point cloud. The misalignment is noticeable in terms of axes, position, and scale. It does not appear to be a simple axis inversion but rather involves a seemingly random rotation.

Steps to Reproduce:

Load an initial point cloud from colmap (It has proper alignment parallel to the axis since it comes from synthetic data)

• Generate the Gaussian it doesn't matter if you use Default or MCMC strategies.
• Compare the Gaussian's orientation, position, and scale with the original point cloud.
• Expected Outcome: The Gaussian should align in position, orientation, and scale with the initial point cloud.

Actual Outcome: The Gaussian exhibits an undesired rotation and misalignment in axes, position, and scale relative to the point cloud. The result seems to be coherent between trainings and strategies.

[belkakari]

Are you comparing gaussians with the colmap's pointcloud after the optimization or before? Because after the optimization process it is expected to have different number of gaussians, diffeerent positions, colors, opacities, etc. since it is what actually was optimized
However, centers of the gaussians before optimization (right after create_splats_with_optimizers function) should align with the ones in the pointcloud. Is that the case?

Or do you mean a global rotation/scale of the whole pointcloud?