Open Miaosheng1 opened 1 month ago
Hi @Miaosheng1, sorry for the late reply. I have been busy for the past few weeks.
Glad to see that you're trying to apply MVSplat to other datasets. It looks like the normalization operation will significantly affect the depth scale, leading to performance differences.
Below, I listed some suggestions that might help identify the main issues,
scale_factor
?With more details regarding the above-listed questions, we might be able to identify the main issues and figure out how to correctly configure the model in your dataset.
Hi, I'm training the Mvsplat to reconstruct the street scene, and I find a question:
scale_factor /= np.max(np.abs(wordl2camera[:, :3, 3]))
wordl2camera[:, :3, 3] *= scale_factor
The comparison curve of training process is as follows:
Can you provide some explanation for the phenomenon?
Normalize the translation Render Depth:
Unnormalize the translation Render Depth:
Corresponding Image: