Comments (3)
Hi @Daewon-Hwang,
To get SMPL joints you need the original J_regressor which you can find in SMPL pkl files.
Here is a small code snippet showing how to use it:
>>> import pickle as pkl
>>> smpl = pkl.load(open('SMPL_NEUTRAL.pkl', 'rb'), encoding='latin1')
>>> smpl.keys()
dict_keys(['J_regressor_prior', 'f', 'J_regressor', 'kintree_table', 'J',
'weights_prior', 'weights', 'posedirs', 'pose_training_info', 'bs_style',
'v_template', 'shapedirs', 'bs_type'])
>>> smpl['J_regressor'].shape # regressor for original 24 SMPL joints
(24, 6890)
>>> joints = smpl['J_regressor'] @ vertices # predicted vertices of shape (6890, 3)
from vibe.
Thank you very much for the answer.
I obtained a 3D joint as you indicated.
However, these joints are a root-relative joint.
Is there a way to get joints in a global position?
from vibe.
Is there a way to get joints in a global position?
Unfortunately, VIBE predicts root relative pose only.
from vibe.
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from vibe.