Thank you for sharing the great work. I have met some questions when using your method.
Here is a picture (s_01_act_02_subact_01_ca_01_000001) of the visualization of the produced human 3d joint coming from smpl model and human3.6M ground truth.
Though impressive result has been achieved, I still have some questions.
If I want to make the dataset of my own by using your method. What is the camera paras and trans paras like? For example, your method will produce camera_rotation(identity matrix), camera_translation, betas, global_orient, body_pose(32-dim), pose(69-dim). But the camera_rotation and transl for other datasets with smpl values (like 3DPW, Human3.6M) are not identity matrix or none. I am confused with the Figure_2 because I think there may be a rotation transformation missed for the smpl model (otherwise the two skeletion will match perfectly). The paras produced by your method and other method for s_01_act_02_subact_01_ca_01_000001 are list as below,
Thank you for sharing the great work. I have met some questions when using your method.
Here is a picture (s_01_act_02_subact_01_ca_01_000001) of the visualization of the produced human 3d joint coming from smpl model and human3.6M ground truth.
Though impressive result has been achieved, I still have some questions.
If I want to make the dataset of my own by using your method. What is the camera paras and trans paras like? For example, your method will produce
camera_rotation
(identity matrix),camera_translation
,betas
,global_orient
,body_pose
(32-dim),pose
(69-dim). But thecamera_rotation
andtransl
for other datasets with smpl values (like 3DPW, Human3.6M) are not identity matrix or none. I am confused with the Figure_2 because I think there may be a rotation transformation missed for the smpl model (otherwise the two skeletion will match perfectly). The paras produced by your method and other method for s_01_act_02_subact_01_ca_01_000001 are list as below,Thank you.