Comments (2)
ascust
commented on June 15, 2024
@Bai426 Hi, thanks for the interest. The reconstruction process is actually based on the statistical model you use. In this repo, I used BFM, which is a 3DMM model created by scanning many faces. If you want to reconstruct the full head, you need to find a 3DMM model that provides a full head. What the code does here is simply finding the best parameters(shape, expression, poses, etc.) to match the given face images. So long story short, what you can do largely depends on what the face model provides.
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Bai426
commented on June 15, 2024
Yes, that makes sense. Thank you very much for your reply and suggestions.
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Related Issues (20)
- FileNotFoundError: [Errno 2] No such file or directory: 'BFM/BFM09_model_info.mat'
- Rigid fitting have some wrong by BFM2019 data. HOT 4
- I have a question about BFM 2019 data HOT 5
- Error:convert_bfm09_data.py HOT 1
- How to get the face texture? HOT 7
- some question about code HOT 1
- why the 3DMM fitting face does not look like the input image? HOT 3
- Why the face_shape need to minus the mean of meanshape? HOT 1
- Can I put an image folder as input?
- Adapting to other statistical face model? HOT 3
- Could you please share the code to generate the GIF of fitting process ? HOT 4
- Texture refering to vertex colors ? HOT 1
- how to fit to rgbd data HOT 6
- Why should reverse z and puls camera position? HOT 3
- How to output a face with ears and neck๏ผ HOT 11
- UV coordinates for BFM09? HOT 3
- How many bases are in the expression model? HOT 1
- RuntimeError: tensor.H is only supported on matrices (2-D tensors). Got 4-D tensor. HOT 1
- found at least two devices: cuda:0 and cpu HOT 1
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