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Secondly, I have been exploring the PeRFception-ScanNet dataset, and I am trying to find the ground truth labels, but I am failing to do so.
If they are included in the folders, is there a location where we can find them?
If not, are there plans for you to release the ground truth files?
Additionally, since there is no documentation for the PeRFception-ScanNet, can you elaborate on the different numpy arrays (thick.npy and trans_info.npz)?
Thanks in advance for your help.
The text was updated successfully, but these errors were encountered:
As you mentioned, the ground truth semantic labels are currently missing in the PeRFception-ScanNet repository.
We'll upload it as soon as possible and let you know when it is done.
For the last question, trans_info.npz contains some useful metadata (e.g. frame ids that are used in training, the transformation matrix that aligns voxel grid of Plenoxels and the original ScanNet point cloud), and thick.npy is for the point cloud data that we used to initialize the voxel grid as stated in our paper.
First off, thank you for your great contribution.
Secondly, I have been exploring the PeRFception-ScanNet dataset, and I am trying to find the ground truth labels, but I am failing to do so.
If they are included in the folders, is there a location where we can find them?
If not, are there plans for you to release the ground truth files?
Additionally, since there is no documentation for the PeRFception-ScanNet, can you elaborate on the different numpy arrays (thick.npy and trans_info.npz)?
Thanks in advance for your help.
The text was updated successfully, but these errors were encountered: