Skip to content
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.

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

about the training strategy #5

Open
lvZic opened this issue Nov 10, 2022 · 0 comments
Open

about the training strategy #5

lvZic opened this issue Nov 10, 2022 · 0 comments

Comments

@lvZic
Copy link

lvZic commented Nov 10, 2022

  1. In the training, I found the camera params (s, tx, ty) seems not converge, but the mano params could converge normaly. I checked the dataset (freihand and interhand), the camera's focal length differs with each image, and it range from 400mm to 800mm. I wonder if the diversity of focal length in the dataset makes it converge worse?

  2. Also, the solution may be adjusting the loss weight in the training process? just as u do /src/strategies/opt_default.py. I wonder how the converge order, what i mean is which parmas should converge first or last?

  3. The camera params GT and camera loss isnot found in your project, should I remove the camera loss too?

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

1 participant