pix2pix
stylegan
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pix2pix | stylegan | |
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13 | 31 | |
9,859 | 13,898 | |
- | 0.4% | |
0.0 | 0.0 | |
almost 3 years ago | 11 months ago | |
Lua | Python | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
pix2pix
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cGAN (img2img) Translation Applied to 3D Scene Post-Editing
This project uses the pix2pix Image translation architecture (https://phillipi.github.io/pix2pix/) for 3D image post-processing. The goal was to test the 3D applications of this type of architecture.
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trained the model based on dark art sketches. got such bizarre forms of life
It seems like this even would make for a cool website, like pix2pix
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Final Year Project on DCGAN for MNIST: Need Advice from the Wise Minds of Reddit
Most improvements from recent GANs' papers usually tinker with the network architecture or loss functions used. Eg. recent near-human quality StyleGANv2 used progressive growing networks, or the GAN that coined image-to-image translation used modified loss function to better learn mapping between images. You can try explore those two factors
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Grainy output of pix2pix GAN
I remember using the original source https://github.com/phillipi/pix2pix and I really did not modify much. For the face pictures I used 600 train pics and 5 hours (Azure NV6).
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[Hobby Scuffles] Week of March 21, 2021
pix2pix, vid2vid a bit harder to use, especially if you don't know your way around a linux shell. definitely possible to get some cool results though.
stylegan
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StyleGAN-T Nvidia, 30x Faster than SD?
Umm, StyleGAN was the first decent image generation model, and it was producing great images from random seeds 5 years ago. Now, that's with the obvious caveat that each model was trained to produce one specific type of image and it helped immensely if the training images were all aligned the same. Diffusion models are certainly the trendy current architecture for image generation, but AFAIK there's no fundamental theoretical limitation to the output quality of any architecture except the general rule that more parameters is better.
- The Concept Art Association updates their AI-restricting gofundme campaign, revealing their lack of AI understanding & nefarious plans! [detailed breakdown]
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[1812.04948] A Style-Based Generator Architecture for Generative Adversarial Networks
PDF link Landing page
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Innovative Technology NVIDIA StyleGAN2
Code: https://github.com/NVlabs/stylegan
https://arxiv.org/abs/1812.04948 (A Style-Based Generator Architecture for Generative Adversarial Networks)
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Technoalchemy - a short spiritual book combining GPT-3 text and art made with StyleGAN + other ML techniques
Check out the PDF here I've been calling this "the first spiritual guidebook written by an AI". The text was written almost entirely with GPT-3, minus the couple of paragraphs I wrote as prompt. The art was made with various tools - for instance, the cover was made in part with Aphantasia (CLIP+FFT), the title page is an old public domain photo colorized with DeOldify, the faces made with StyleGAN, both standalone and via Artbreeder. Let me know what you think - I have a couple bigger projects building off of the techniques I used, and I would appreciate any feedback!
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[Hobby Scuffles] Week of March 21, 2021
stylegan this is the tech behind all those "this ___ does not exist" sites. it's actually surprisingly easy to use if you know how to use the terminal (and preferably a little bit of python).
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NEW PYTHON PACKAGE: Sync GAN Art to Music with "Lucid Sonic Dreams"!
Clone stylegan
What are some alternatives?
stylegan2 - StyleGAN2 - Official TensorFlow Implementation
CycleGAN - Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.
lucid-sonic-dreams
naver-webtoon-faces - Generative models on NAVER Webtoon faces
DeOldify - A Deep Learning based project for colorizing and restoring old images (and video!)
aphantasia - CLIP + FFT/DWT/RGB = text to image/video
ffhq-dataset - Flickr-Faces-HQ Dataset (FFHQ)
awesome-pretrained-stylegan2 - A collection of pre-trained StyleGAN 2 models to download
perspective-change - cGAN Based 3D Scene Re-Compositing
awesome-image-translation - A collection of awesome resources image-to-image translation.
art-DCGAN - Modified implementation of DCGAN focused on generative art. Includes pre-trained models for landscapes, nude-portraits, and others.