Li Chen

And may I also know the resolution you are using for the voxelization process?

Hi @trumDog, The full joint list for the MPI-INF-3DHP dataset is {'spine3', 'spine4', 'spine2', 'spine', 'pelvis', 'neck', 'head', 'head_top', 'left_clavicle', 'left_shoulder', 'left_elbow', 'left_wrist', 'left_hand', 'right_clavicle', 'right_shoulder', 'right_elbow', 'right_wrist', 'right_hand', 'left_hip',...

Your description sounds ok, have you ever visualized the estimated poses and are they looks reasonable. Btw, the numbers reported in our paper is based best hypothesis.

Seems that you have a different joint index (with the 14th joint being the root joint)?

Sorry that I do not have time to clean up the code for this part currently. Can you try to use the statistics of 'annot3' instead of 'univ_annot3' to unnormalize...

I did not use other tricks here. I use the mean and std of the 'annot3' data for normalization and unnormalization, and then use a threshold of 150mm (which corresponds...

Hi @trumDog, Thanks for pointing out, I used the statistics of the valid set for the normalization. I tried the statistics of human3.6 just now, and it gives a lower...

Hi @trumDog, We first select the hypotheses under different viewpoints by using the consistent constraint. Then we take the average value of the selected hypotheses under different viewpoints for the...

Hi @jutanke, Sorry for the confusion. I used the script provided by [@uoguelph-mlrg](https://github.com/uoguelph-mlrg/mhmublv) to convert the original data. The data has been downsampled to 30Hz as they described in their...

Hi @dfxyy, sorry for the late reply. We did not use the 'walking_extra' to keep the number of sequence for each action the same.