gan-vae-pretrained-pytorch
GFPGAN-for-Video-SR
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| gan-vae-pretrained-pytorch | GFPGAN-for-Video-SR | |
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| 1 | 1 | |
| 162 | 31 | |
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| 0.0 | 0.0 | |
| over 2 years ago | 10 months ago | |
| Jupyter Notebook | Jupyter Notebook | |
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gan-vae-pretrained-pytorch
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DCGAN (CIFAR-10) Generating fake images is easy, but how to also output the class label (1 to 10) with the fake generated images?
I have this DCGAN model (https://github.com/csinva/gan-vae-pretrained-pytorch/tree/master/cifar10_dcgan) which generates fake Cifar-10 images. However I also want to get the intended class label output with the fake generated images. How can I do this? This model which I found only generates fake images but doesn't know what class the generated images belong to.
GFPGAN-for-Video-SR
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I Upscaled Linus's first video (Better results than Topaz Labs)
If you want to upscale your own videos , check out my colab notebook to do it for free : https://github.com/GeeveGeorge/GFPGAN-for-Video-SR
What are some alternatives?
AvatarGAN - Generate Cartoon Images using Generative Adversarial Network
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pytorch-GAT - My implementation of the original GAT paper (Veličković et al.). I've additionally included the playground.py file for visualizing the Cora dataset, GAT embeddings, an attention mechanism, and entropy histograms. I've supported both Cora (transductive) and PPI (inductive) examples!
Real-ESRGAN-Video-Batch-Process - Upscale any number of videos using this colab notebook!
AnimeGAN - Generating Anime Images by Implementing Deep Convolutional Generative Adversarial Networks paper
ganspace - Discovering Interpretable GAN Controls [NeurIPS 2020]
AI-For-Beginners - 12 Weeks, 24 Lessons, AI for All!
License-super-resolution - A License Plate Image Reconstruction Project in Tensorflow2
Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning - My Computer Vision project from my Computer Vision Course (Fall 2020) at Goethe University Frankfurt, Germany. Performance comparison between state-of-the-art Object Detection algorithms YOLO and Faster R-CNN based on the Berkeley DeepDrive (BDD100K) Dataset.
Real-ESRGAN-ncnn-vulkan - NCNN implementation of Real-ESRGAN. Real-ESRGAN aims at developing Practical Algorithms for General Image Restoration.
dnn_from_scratch - A high level deep learning library for Convolutional Neural Networks,GANs and more, made from scratch(numpy/cupy implementation).
JoJoGAN - Official PyTorch repo for JoJoGAN: One Shot Face Stylization