I wonder why the SMPLParamRegressor don't go in an iterative way to give the final smpl param? Like described in paper End-to-end Recovery of Human Shape and Pose?
I mean at test time, by using a 2D skeleton detector, we can first align the input body to the same orientation, once we get the output smpl (theta0, beta0) and camera param, we can fix the beta0 and only update theta0 (taking theta0 as initial value) according to the loss between the detected skeleton and the projected smpl skeleton, I think the result should be much more better for testing images.
I'm I right? Are there any shortcomings leaving out efficiency?
Looking forward to any discussion with you !!! ;p
I wonder why the SMPLParamRegressor don't go in an iterative way to give the final smpl param? Like described in paper End-to-end Recovery of Human Shape and Pose?
I mean at test time, by using a 2D skeleton detector, we can first align the input body to the same orientation, once we get the output smpl (theta0, beta0) and camera param, we can fix the beta0 and only update theta0 (taking theta0 as initial value) according to the loss between the detected skeleton and the projected smpl skeleton, I think the result should be much more better for testing images.
I'm I right? Are there any shortcomings leaving out efficiency?
Looking forward to any discussion with you !!! ;p