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Analyzing and Improving the Image Quality of StyleGAN

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Xander Steenbrugge: Whoa, StyleGANv2 is out! - Significantly better samples (better FID scores & reduced artifacts) - No more progressive growing - Improved Style-mixing - Smoother interpolations (extra regularization) - Faster training Paper: https://arxiv.org/abs/1912.04958 Github: https://github.com/NVlabs/stylegan2 https://t.co/5Cnlg9j91V

6 replies, 611 likes


roadrunner01: Analyzing and Improving the Image Quality of StyleGAN pdf: https://arxiv.org/pdf/1912.04958.pdf abs: https://arxiv.org/abs/1912.04958 github: https://github.com/NVlabs/stylegan2 https://t.co/QK8ROJl9J5

5 replies, 295 likes


Ming-Yu Liu: StyleGAN2 is out. https://arxiv.org/abs/1912.04958

1 replies, 213 likes


Alexia Jolicoeur-Martineau: NVIDIA basically fixed most of the issues with their architecture. They now use gradient penalty only 1/16 of the times making it much faster and they replaced progressive growing by a modified MSG-GAN (@AnimeshKarnewar). The amount of work done is insane for one single paper.

3 replies, 173 likes


Jonathan Fly 👾: StyleGAN 2: Mostly We Got Rid of The Blobs Also: No 'phase artifacts' (I hadn't noticed them but obvious in retrospect), easier-to-navigate latent spaces mean better encoding, and ~25% more efficient. pdf: https://arxiv.org/abs/1912.04958 code (coming-later): https://github.com/NVlabs/stylegan2 https://t.co/nw2ddLq0of

2 replies, 137 likes


Jaakko Lehtinen: This just in: we have updated the #StyleGAN2 paper with estimates of total GPU time and energy consumption, with a breakdown over the different facets of the research project. See new Appendix F and Table 5. https://arxiv.org/abs/1912.04958

1 replies, 64 likes


Jaakko Lehtinen: #StyleGAN2 out now https://arxiv.org/abs/1912.04958

1 replies, 57 likes


小猫遊りょう(たかにゃし・りょう): 論文 Analyzing and Improving the Image Quality of StyleGAN https://arxiv.org/abs/1912.04958 StyleGAN2 — Official TensorFlow Implementation https://github.com/NVlabs/stylegan2

1 replies, 43 likes


Drew Harwell: These are all computer-generated faces. (From new Nvidia AI research: https://arxiv.org/pdf/1912.04958.pdf.) https://t.co/fm36PeikhB

1 replies, 37 likes


Miles Brundage: Interesting: "It turns out that our improvements to StyleGAN make it easier to detect generated images using projection-based methods, even though the quality of generated images is higher." https://twitter.com/ak92501/status/1204937687649673218?s=20

1 replies, 35 likes


Jane Lytvynenko 🤦🏽‍♀️🤦🏽‍♀️🤦🏽‍♀️: this tech has gotten so much better in such a short span of time 😬

5 replies, 32 likes


Mr.Deeds⭐⭐⭐: AI created faces, all these people don't exist... refresh the browser to generate a new face. Computer Vision and Pattern Recognition #StyleGAN2 #GAN #DeepFakes https://arxiv.org/abs/1912.04958 https://thispersondoesnotexist.com/ https://t.co/lb4anDAW0K

5 replies, 22 likes


Giorgio Patrini 🛡️👾: This analysis is excellent @benimmo but please careful: some of these telltales are already solved by StyleGAN v2, and won't be there at the next disinfo automated campaign exploiting synthetic photos https://arxiv.org/abs/1912.04958

1 replies, 21 likes


Kyle McDonald: NVIDIA just released the latest tech for image generation. I can still find a few artifacts if i zoom in at 1024x1024, but i would guess we’ve passed human recognition at 512x512 https://arxiv.org/abs/1912.04958 https://t.co/REy87VqamX

2 replies, 19 likes


Philip Vollet: AI is heading over into the Adobe core products! Like style transfer via GANs Generative Adversarial Networks super amazing to see this. Blog http://adobe.ly/37pqsxs Powered by Adobes StyleGAN2 implementation GitHub https://github.com/NVlabs/stylegan2 Paper https://arxiv.org/abs/1912.04958 https://t.co/n3duNjSb64

1 replies, 14 likes


Koichi Hamada: StyleGAN2: "Analyzing and Improving the Image Quality of StyleGAN" - Github: https://github.com/NVlabs/stylegan2 - ArXiv: http://arxiv.org/abs/1912.04958 - Video: https://www.youtube.com/watch?v=c-NJtV9Jvp0

0 replies, 9 likes


Jeremy Cowles: Update to StyleGAN focused on analyzing the previous architecture, I'm super curious to see what they found: https://arxiv.org/abs/1912.04958

1 replies, 8 likes


Emmett Macfarlane: Whoa... https://twitter.com/drewharwell/status/1205116111693455360

0 replies, 7 likes


jess: @LargeCardinal On a similar note, Nvidia released StyleGAN2 a few months back. The quality and accessibility of these images is second to none, especially with sites such as http://thispersondoesnotexist.com paper's worth reading: https://arxiv.org/abs/1912.04958 also have a git repo: https://github.com/NVlabs/stylegan2

1 replies, 6 likes


Shanthi Kalathil: With even just a tiny bit of imagination, it becomes clear that current efforts to develop widespread digital literacy and strengthen democratic resilience are likely to be quickly outpaced.

0 replies, 6 likes


Daisuke Okanohara: StyleGAN2:1) Replace Instance Norm with Weight Norm to remove droplet artifact 2) Introduce path length regularization to minimize perceptual path length 3) skip-connected generator, residual discriminator, no progressive growing. https://arxiv.org/abs/1912.04958 https://www.youtube.com/watch?v=c-NJtV9Jvp0

0 replies, 5 likes


Andy Baio: More info in this thread if you want to learn more. https://twitter.com/xsteenbrugge/status/1205108677641981952?s=21

1 replies, 5 likes


Aaron Gokaslan: StyleGAN v2 is out!

0 replies, 3 likes


Roelof Pieters: StyleGan is back with a V2 overhaul! - Much better quality and FID scores - Removing artefacts by demodulation - No progressive growing - New MSG-GAN architecture - Quicker training Paper: https://arxiv.org/abs/1912.04958 Code: https://github.com/NVlabs/stylegan2 https://t.co/OCt7ZNFXwr

0 replies, 2 likes


Málaga Artificial Intelligence: StyleGANv2. The authors did a big homework and fixed "light spots" and "burnt skin" artifacts. Also, they proposed an improved method for finding real images in latent space (but still via backprop). 🔎 http://github.com/NVlabs/stylegan2 📝 http://arxiv.org/abs/1912.04958 📉 @loss_function_porn https://t.co/jJNpMSSlXj

0 replies, 2 likes


Tarik Hammadou: Analyzing and Improving the Image Quality of StyleGAN #deeplearning #AI #computervision https://arxiv.org/pdf/1912.04958.pdf

0 replies, 2 likes


Ruqiya: تحسين لل styleGAN ورقة نشرت بهذا الشهر 3 ديسمبر 2019 عنوانها Analyzing and Improving the Image Quality of StyleGAN على الرابط https://arxiv.org/abs/1912.04958 حاليا مهتمة بال GANs

0 replies, 1 likes


Parand Darugar: StyleGAN, the system that creates those eerily realistic portraits you saw at https://thispersondoesnotexist.com/ , has been updated to be even more effective: Video: https://www.youtube.com/watch?v=c-NJtV9Jvp0 Paper: https://arxiv.org/abs/1912.04958 So many cool things coming out of NeurIPS, wish I was there.

0 replies, 1 likes


Deeptrace: @GlennF @razhael Yet it is important to point out that those signs may soon disappear. Version 2 of the StyleGAN model was open sourced just days ago, and claimed to have solved some of the known issues in generation. https://twitter.com/GiorgioPatrini/status/1208171954278207489?s=20

1 replies, 0 likes


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Found on Dec 12 2019 at https://arxiv.org/pdf/1912.04958.pdf

PDF content of a computer science paper: Analyzing and Improving the Image Quality of StyleGAN