Image-to-Image Translation in PyTorch
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Updated
May 14, 2024 - Python
Generative adversarial networks (GAN) are a class of generative machine learning frameworks. A GAN consists of two competing neural networks, often termed the Discriminator network and the Generator network. GANs have been shown to be powerful generative models and are able to successfully generate new data given a large enough training dataset.
Image-to-Image Translation in PyTorch
GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.
12 Weeks, 24 Lessons, AI for All!
🧑🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
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A MNIST-like fashion product database. Benchmark 👇
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A tensorflow implementation of "Deep Convolutional Generative Adversarial Networks"
A list of all named GANs!
This repo contains the source code in my personal column (https://zhuanlan.zhihu.com/zhaoyeyu), implemented using Python 3.6. Including Natural Language Processing and Computer Vision projects, such as text generation, machine translation, deep convolution GAN and other actual combat code.
Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.
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Image-to-image translation with conditional adversarial nets
Deep Learning and Reinforcement Learning Library for Scientists and Engineers
Released June 10, 2014