Comments (5)
注明出处和作者即可
from white-box-cartoonization.
我们公司想用在芯片发布会上展示本论文的效果,是否注明出处和作者即可
from white-box-cartoonization.
我的邮箱是[email protected],方便详细交流一下
from white-box-cartoonization.
@qiqiyang2016 仅展示效果是ok的,不过建议还是跑vgg,mobilenet这种大家都用的常用网络
from white-box-cartoonization.
@qiqiyang2016 仅用于芯片能力展示,非商用。算法来自Xinrui Wang, Jinze Yu, Learning to cartoonize using white-box cartoon representations, CVPR2020.
或者其他正规的文献引用格式也可以。
from white-box-cartoonization.
Related Issues (20)
- Opening the Door to White Box Cartoonization HOT 1
- image[k] = (image[k]+1) * 127.5 HOT 2
- 怎么训练模型
- AttributeError: module 'network' has no attribute 'unet_generator' HOT 1
- TypeError: only size-1 arrays can be converted to Python scalars
- Questions for API integration
- 'NoneType' object has no attribute 'astype' HOT 2
- TypeError: only size-1 arrays can be converted to Python scalars
- @SystemErrorWang Nice job, but when I used my own dataset to train, It has a bug in utils.py's function simple_superpixel 'batch_out = Parallel(n_jobs=num_job)(delayed(process_slic)\
- make images more cartoonized
- Ported to TFJS and running in Browser using WebGL backend or in NodeJS with CUDA
- ModuleNotFoundError: No module named 'tensorflow.contrib'
- How to achieve an oil painting effect? HOT 1
- Questions about the material surface. I want more details when output HOT 1
- no healthy upstream
- QQ加不了? HOT 2
- Commercial Use HOT 1
- How to use it? Does it work?
- How guided filter is working where?
- Learning Curve
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