google / lecam-gan Goto Github PK
View Code? Open in Web Editor NEWRegularizing Generative Adversarial Networks under Limited Data (CVPR 2021)
License: Apache License 2.0
Regularizing Generative Adversarial Networks under Limited Data (CVPR 2021)
License: Apache License 2.0
The model file is not accessible and call to model file raises the following exception.
model_path=gs://robust-gan/lc-biggan-imagenet128-100/240000
batch_size=2
rm: cannot remove '/tmp/models/*': No such file or directory
ServiceException: 401 Anonymous caller does not have storage.objects.list access to the Google Cloud Storage bucket.
CommandException: 1 file/object could not be transferred.
download model file to :
Can you please provide the file or share where can I get it?
Hello!
Thanks for the great paper and code!
Unfortunately I am having some issues with integrating the lecam_loss.py with the original stylegan2-ada repo.
I tried hardcoding the functionality of the lecam_loss.py function into the stylegan2 loss in here. It trains but it starts producing aliens and in it quite quickly turns into green images.
Could you please clarify how it is done in more detail?
Hi,
Why two exponential moving average variables are initiated as 1000?
Any intuition about this initiation?
Thx
Hello, thanks for sharing this helpful repo! I found that in your code the decay factor is 0.9 which is reported as 0.99 in the paper. Although this is not a critical problem, which value should I exactly use to better reproduce the performance in the paper?
Paper:
We fix the decay factor γ to 0.99 in all experiments.
Code:
lecam-gan/third_party/utils.py
Line 638 in f9af948
Best.
Hi
I noticed there is only the code for Lecam regularizer in the StyleGAN2 folder. Is the full implementation not available in the repo? Are we supposed to manually add the regularizer to the official StyleGAN2 code ourselves?
Hi,
It seems like the baseline results in your paper are different from the results in ADA/DA. For example, FID reported for Cifar10 is 5.33 in ADA and 2.68 in your paper. Please advise.
How to train the Lecam-gan on the low-shot image generation datasets,THX.
Hi!
The paper link in the readme points to https://github.com/google/lecam-gan/blob/master, which I assume is a mistake. My first thought was that this was maybe by design since CVPR2021 is in June and so the paper isn't public yet, but then I found it here, so I guess this is not the case.
Thanks for your work btw!
Thank you for making your implementation available, I'm quite excited to apply the regularizer to ongoing projects.
There was some discussion online recently about a possible mismatch between Eqn 4 in a public preprint of the paper (available here) and the code implementation at these lines: {tf, pytorch}.
Could you please clarify if there's supposed to be a ReLU (present in the code but not the preprint) in Eqn. 4 as well? Thanks again!
Hi,thanks for your great work.
Do you have the version implemented by Pytorch?
What does 'Third_party' refer to in the stylegan2 implementation?
The formula (4) in the paper is
R_{LC}= E_{x∼T}[||D(x)−\alpha_{F}||^2]+ E_{z∼p_z}[||D(G(z))−\alpha_R||^2]
but according to my understanding, this will not make the result converge to a certain point stably, but will cause the result to oscillate, and this does not conform to the legend (2) in the paper, is this a clerical error?
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.