Comments (2)
Thanks. What a marvellous idea!
from ostec.
Hi,
A very good question. render_uv_image
function basically unwrap the face into a UV space given a 3D face reconstruction (i.e. dense landmarks). In order to know which parts of UV texture map need completion, we first run a face segmentation/masking on 2D image and then map it to the UV texture map. To avoid running UV extraction (i.e. which is arasterization process) twice, I concat the masking to the RGB image and then seperate.
img_uv_src.pixels[3]<0.5
inversing the map as well as removing any non-binary outputs caused by the interpolation.
Later we use this UV mask here to remove segmented part of the face from UV texture map.
Hope this answers your question,
Baris
from ostec.
Related Issues (20)
- How to obtain the visibility mask of the raw face image HOT 2
- How to render correctly? HOT 3
- Unable to reproduce paper results HOT 3
- Download failed, there are other download paths? HOT 5
- I would like to know how to get the de-occluded frontal face image HOT 2
- Crashing while running the program: same configuration that this repository was tested with HOT 1
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- Will the repository work with CUDA 11? HOT 7
- Why dense landmarks need to minus 5?
- args parameters HOT 1
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- IndexError: index 0 is out of bounds for axis 0 with size 0` HOT 2
- Error in conda environment HOT 1
- Training Step
- run parameter -f unrecognized
- texture and shape are not aligned
- i get ResolvePackageNotFound:error i'm trying on Windows
- tensorflow_core/include/Eigen/Core:28:12: fatal error: cuda/std/complex: No such file or directory
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from ostec.