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

Generate my own image? #25

Closed
kayakaracakaya opened this issue Oct 23, 2019 · 1 comment
Closed

Generate my own image? #25

kayakaracakaya opened this issue Oct 23, 2019 · 1 comment

Comments

@kayakaracakaya
Copy link

Firstly, thanks for the work and sorry for my low knowledge.

I want to give two specific image, source and target, and transfer pose of source to target. How can i do this, can you explain to me step by step?

Thanks.

@layumi
Copy link
Contributor

layumi commented Oct 31, 2019

Hi @kayakaracakaya
Thanks for your attention on our papers.
You mentioned that you want to transfer the pose of the source to target.
Do you want to preserve the identity of the source image or target image?

If you would like to generate the Fig. 5 or Fig.9 in the paper, you may check

visual_tools/show_smooth.py generates Figure 5 of the paper.

visual_tools/show_smooth_structure.py generates Figure 9 of the paper.

For DG-Net, we focus on the changing appearance of the foreground object, i.e., the cloth of the person.
So it is not optimal for changing the pose.

For changing pose, I recommend several papers as follows. You may refer to them. Hope them could help you.

[1] Wei L, Zhang S, Gao W, et al. Person transfer gan to bridge domain gap for person re-identification CVPR 2018
[2] https://github.com/charliememory/Pose-Guided-Person-Image-Generation

@layumi layumi closed this as completed Nov 27, 2019
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

2 participants