vision-aided-gan
joliGEN
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| vision-aided-gan | joliGEN | |
|---|---|---|
| 3 | 4 | |
| 365 | 196 | |
| - | 5.1% | |
| 0.0 | 9.5 | |
| over 1 year ago | 8 days ago | |
| Python | Python | |
| MIT License | GNU General Public License v3.0 or later |
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vision-aided-gan
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[D] Is the GAN architecture currently old-fashioned?
If you are looking for more traditional noise -> xxx GANs, go for https://github.com/autonomousvision/projected_gan/. Another recent work is https://github.com/nupurkmr9/vision-aided-gan.
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🟢🌿 Power Up your GameStop Wallet with the Ability to Create New Marijuana Strains - GAN Interactive NFT - 7410 Available 🟢🌿
Interactive GAN NFT trained with a vision-guided StyleGAN2 using this repo. Every nug/strain generation is unique and you can also create interpolations (takes around 2 minutes to render) between two nugs/strains. If you would like to help me distribute these please specify whether you would like 50, 100, 250, or 500! Thank you so much!
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In The Latest AI Research, CMU And Adobe Researchers Propose An Elegant Emsembling Mechanism For GAN Training That Improves FID by 1.5x to 2x On The Given Dataset
Github: https://github.com/nupurkmr9/vision-aided-gan
joliGEN
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[D] Question about using diffusion to denoise images
Absolutely, I do second this, Palette is what you are looking for. We have a modified version in JoliGAN, with PR for various conditioning, including masks and sketches, cf https://github.com/jolibrain/joliGAN/pull/339
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[D] Is the GAN architecture currently old-fashioned?
We use https://github.com/jolibrain/joliGAN which is a lib for image2image with additional "semantic" constraints. I.e. when there's a need to conserve labels, physics, anything between the two domains. This lib aggregates and improves on existing works.
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[P] Real-time AR for jewelry virtual try on that looks real, done with joliGAN, based on a few 2D videos and no 3D model
We thought we'd share some technical details since the underlying code, JoliGAN is Open Source, https://github.com/jolibrain/joliGAN
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[D] Augmentation in GAN
Look at DiffAug, deceive, and such. It's all implemented into Joligan, https://github.com/jolibrain/joliGAN We're able to train with small datasets, though not always optimally. With large datasets results are outstanding.
What are some alternatives?
Anime2Sketch - A sketch extractor for anime/illustration.
hifigan-denoiser - HiFi-GAN: High Fidelity Denoising and Dereverberation Based on Speech Deep Features in Adversarial Networks
const_layout - Official implementation of the MM'21 paper "Constrained Graphic Layout Generation via Latent Optimization" (LayoutGAN++, CLG-LO, and Layout evaluation)
PassGAN - A Deep Learning Approach for Password Guessing (https://arxiv.org/abs/1709.00440)
anycost-gan - [CVPR 2021] Anycost GANs for Interactive Image Synthesis and Editing
cycle-gan-pytorch - This repository contains an implementation of the Cylce-GAN architecture for style transfer along with instructions to train on an own dataset.
projected-gan - [NeurIPS'21] Projected GANs Converge Faster
dnn_from_scratch - A high level deep learning library for Convolutional Neural Networks,GANs and more, made from scratch(numpy/cupy implementation).
pytorch-CycleGAN-and-pix2pix - Image-to-Image Translation in PyTorch
deepdetect - Deep Learning API and Server in C++14 support for Caffe, PyTorch,TensorRT, Dlib, NCNN, Tensorflow, XGBoost and TSNE
StyleSwin - [CVPR 2022] StyleSwin: Transformer-based GAN for High-resolution Image Generation
nni - An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.