fanziapril / mvfnet Goto Github PK
View Code? Open in Web Editor NEWPytorch code for paper: MVF-Net: Multi-View 3D Face Morphable Model Regression
License: MIT License
Pytorch code for paper: MVF-Net: Multi-View 3D Face Morphable Model Regression
License: MIT License
I cannot locate the model shape mat file it is not in the 3ddfa zip
Thank you for your job.
How to do Differentiable Rendering?Use https://github.com/google/tf_mesh_renderer?
Hi,
Thanks for your excellent work. I want to project the model to the front image of three input images, could you please tell me how to project the model to front image?
Thanks!
Hello, I download the code of 3DDFA, but there is only the file Model_Expression.mat. May I ask where the file Model_shape.mat is ?
Thankyou~
No texture found after construction
Maybe it's a stupid question...
@Fanziapril, Hi, I am appreciated with your great job? but I have some question.
How could I get a absolute frontal rendered image given the generated 3d face model and a InputB image which is a relative frontal face?
modelshape.mat is hard to get
only Model_Expression.mat in 3DDFA.
what should I do?
Sorry,For some reason(vpn is error...0_0),I can't download CNN model in dropbox,and could you save it in Baiduyun or other address?
When I tried to install with pip install torchvision, it kept deleting pytorch 0.4.0 and installing recent version.
Hi. I've tried your model on florence dataset and do a quantitative experiment. However, in my test your method is worse than Genova et al.. I wonder if there is some limitations i did not notice. For example, do you allow left and right images with large poses (yaw angles larger than 60 degrees) ? By the way, florence dataset has multiple images for a single subject under different scenes, do you use only 3 images of a subject for evaluation in your paper?
how to get textured output with the ply
How to install the code:
hi,
I can't find 01_MorphableModel.mat in (1),just get BaselFaceModel.
Hi! Thanks for your great work in 3D face reconstruction!
I have a question about the processing of MICC Florence dataset.
How did you process the scan results, especially the crop step? Because I find it difficult to find the nose point accurately T_T...
Thank you for your job.
I found that there are seven pose parameters. What do they mean respectively?
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