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Hi,Thank you for providing the code,wonderful job.
I feel puzzled about the SMPL pose and shape param sampling mentioned in your paper section 5.1. Does uniform sampling means you not need to fit the CMU data as a mixed-gauss function, just to calculate the mean value and standard deviation to generate virtual shapes for every dims(usually as 10 dims)?
eg: numpy.random.uniform(low,high,size)
Do you provide any code or suggestion for this part? Thanks a lot.
The text was updated successfully, but these errors were encountered:
Hi,Thank you for providing the code,wonderful job.
I feel puzzled about the SMPL pose and shape param sampling mentioned in your paper section 5.1. Does uniform sampling means you not need to fit the CMU data as a mixed-gauss function, just to calculate the mean value and standard deviation to generate virtual shapes for every dims(usually as 10 dims)?
eg: numpy.random.uniform(low,high,size)
Do you provide any code or suggestion for this part? Thanks a lot.
The text was updated successfully, but these errors were encountered: