Comments (2)
Yes. The mean and standard deviation of x are implemented by layernorm without learnable affine parameters. The output dimensions are both 1x1xC. Please follow this repository for the exact implementation, we will release the code and pre-trained model after the paper is accepted.
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Thanks!
Looking forward to your code and model.
from hairclip.
Related Issues (20)
- About Video Hair Editing HOT 1
- code
- question of split database(train.pt and test.pt)
- What this mean in
- What is the truncation for in function configure_datasets of coach.py?
- How to slove the problem "train.py: error: the following arguments are required: --hairstyle_description, --color_description " when i run code in Colab? HOT 1
- I notice that image manipulation loss is defined as "1-cos(,) " . But I feel confused that whether i can change that to "-cos"
- F and C
- What is the data set of test input
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- What is the code license? HOT 1
- Will stylegan inversion encoder be trained? HOT 2
- How to change the hairstyle of a given image with a image containing the target hairstyle?
- local variable 'shape' referenced before assignment
- How many images were used to calculate the three metrics IDS, PSNR, and SSIM derived from Table 1?
- Inference on image data without converting to e4e HOT 1
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