Implementation of Gans

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Deep Learning GAN
Overview

GAN

Generative Adverserial Networks are an approach to generative data modelling using Deep learning methods.

I have currently implemented :

  • DCGAN on CIFAR dataset.
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StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.
StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.

StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.

[CVPR 2021] Anycost GANs for Interactive Image Synthesis and Editing
[CVPR 2021] Anycost GANs for Interactive Image Synthesis and Editing

Anycost GAN video | paper | website Anycost GANs for Interactive Image Synthesis and Editing Ji Lin, Richard Zhang, Frieder Ganz, Song Han, Jun-Yan Zh

Code for the paper
Code for the paper "Training GANs with Stronger Augmentations via Contrastive Discriminator" (ICLR 2021)

Training GANs with Stronger Augmentations via Contrastive Discriminator (ICLR 2021) This repository contains the code for reproducing the paper: Train

EigenGAN Tensorflow, EigenGAN: Layer-Wise Eigen-Learning for GANs
EigenGAN Tensorflow, EigenGAN: Layer-Wise Eigen-Learning for GANs

Gender Bangs Body Side Pose (Yaw) Lighting Smile Face Shape Lipstick Color Painting Style Pose (Yaw) Pose (Pitch) Zoom & Rotate Flush & Eye Color Mout

This is the codebase for Diffusion Models Beat GANS on Image Synthesis.

This is the codebase for Diffusion Models Beat GANS on Image Synthesis.

[CVPR 2020] Interpreting the Latent Space of GANs for Semantic Face Editing
[CVPR 2020] Interpreting the Latent Space of GANs for Semantic Face Editing

InterFaceGAN - Interpreting the Latent Space of GANs for Semantic Face Editing Figure: High-quality facial attributes editing results with InterFaceGA

Synthesizing and manipulating 2048x1024 images with conditional GANs
Synthesizing and manipulating 2048x1024 images with conditional GANs

pix2pixHD Project | Youtube | Paper Pytorch implementation of our method for high-resolution (e.g. 2048x1024) photorealistic image-to-image translatio

PyTorch inference for
PyTorch inference for "Progressive Growing of GANs" with CelebA snapshot

Progressive Growing of GANs inference in PyTorch with CelebA training snapshot Description This is an inference sample written in PyTorch of the origi

Codebase for Diffusion Models Beat GANS on Image Synthesis.

Codebase for Diffusion Models Beat GANS on Image Synthesis.

Owner
Sibam Parida
3rd year Undergraduate at VNIT,Nagpur
Sibam Parida
This is the PyTorch implementation of GANs N’ Roses: Stable, Controllable, Diverse Image to Image Translation

Official PyTorch repo for GAN's N' Roses. Diverse im2im and vid2vid selfie to anime translation.

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[CVPR 2021] Pytorch implementation of Hijack-GAN: Unintended-Use of Pretrained, Black-Box GANs

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A PyTorch implementation of ViTGAN based on paper ViTGAN: Training GANs with Vision Transformers.

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PyTorch implementation of Progressive Growing of GANs for Improved Quality, Stability, and Variation.

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PyTorch implementation of VAGAN: Visual Feature Attribution Using Wasserstein GANs

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GAN encoders in PyTorch that could match PGGAN, StyleGAN v1/v2, and BigGAN. Code also integrates the implementation of these GANs.

MTV-TSA: Adaptable GAN Encoders for Image Reconstruction via Multi-type Latent Vectors with Two-scale Attentions. This is the official code release fo

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Implementation supporting the ICCV 2017 paper "GANs for Biological Image Synthesis"

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A pytorch implementation of Paper "Improved Training of Wasserstein GANs"

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PyTorch implementation for OCT-GAN Neural ODE-based Conditional Tabular GANs (WWW 2021)

OCT-GAN: Neural ODE-based Conditional Tabular GANs (OCT-GAN) Code for reproducing the experiments in the paper: Jayoung Kim*, Jinsung Jeon*, Jaehoon L

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PyTorch Implementation of DiffGAN-TTS: High-Fidelity and Efficient Text-to-Speech with Denoising Diffusion GANs

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