New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

proplem of Integral Pose Regression #42

Open

wangm-word opened this issue Aug 12, 2021 · 1 comment

wangm-word commented Aug 12, 2021 •

edited

Loading

thank you for your great work!
I want to know,when you train it ?the 2D data miss "Z" coordinate value,how to deal with it?

Collaborator

lck1201 commented Aug 13, 2021 •

edited

Loading

generate a mask applying on Z, see

integral-human-pose/pytorch_projects/common_pytorch/dataset/mpii.py

Line 171 in ad3f875

'joints_3d_vis': jts_3d_vis,

integral-human-pose/pytorch_projects/common_pytorch/common_loss/weighted_mse.py

Line 13 in ad3f875

out = out * weights

in this way, loss of z won't affect BP.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment