Comments (7)
thmoa
commented on August 15, 2024
like all deep learning based works: variance in the training data
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OOF-dura
commented on August 15, 2024
like all deep learning based works: variance in the training data
Thanks! Does that mean during training, you just used RGB images without any preprocessing?
Thx again!
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thmoa
commented on August 15, 2024
Please refer to the paper...
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OOF-dura
commented on August 15, 2024
Please refer to the paper...
OK. But I find when you map the color in image to the UV map based on the result of densepose, the color of the skin is a little blue.
which is different from the picture in the paper:
Thanks!
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thmoa
commented on August 15, 2024
RGB vs BGR.
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OOF-dura
commented on August 15, 2024
Thanks!
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lemon1220
commented on August 15, 2024
@OOF-dura @thanks!
hello, can you kindly teach me how to gernerate the UVmap just like the following ?
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Related Issues (17)
- How to register the SMPL model against your scans HOT 1
- Python 3 support? HOT 1
- how get a texture for this model? HOT 1
- How do you generate the canonical UV maps in your papers HOT 1
- how to get different poses in the result? HOT 2
- Generating UV textures from 3D pose detector HOT 1
- UV map details HOT 1
- installation issues HOT 1
- Why do all the results have the same pose? HOT 5
- what is the best visualizer to check the ourput obj and pkl files? HOT 2
- Texture generation for the 3d model HOT 1
- How to generate dp_uv_lookup_256.npy? HOT 4
- UV map synthetization HOT 1
- thank you for you work HOT 7
- posed mesh
- Training code. HOT 1
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