PyTorch Implementation of CycleGAN and SSGAN for Domain Transfer (Minimal)
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Updated
May 27, 2017 - Python
PyTorch Implementation of CycleGAN and SSGAN for Domain Transfer (Minimal)
A deep learning model to age faces in the wild, currently runs at 60+ fps on GPUs
PyTorch implementation of the paper "Semantically Tied Paired Cycle Consistency for Zero-Shot Sketch-based Image Retrieval", CVPR 2019.
Developing an image editing application to edit images to have a desired attribute using Generative Adversarial Networks(DCGAN and CycleGAN) (https://tandon-a.github.io/Image-Editing-using-GAN/)
Translating Synthetic RIRs to Real RIRs
Pixel-level domain adaptation: A study case on generating parking-slot image samples.
AI-enabled Interior decoration, powered by CycleGANs. Built for @NextTechLabAP's #9Hacks!
Pytorch implementation of Self Attentive Adversarial Stain Normalization (SAASN).
Reproducing PARALLEL-DATA-FREE VOICE CONVERSION USING CYCLE-CONSISTENT ADVERSARIAL NETWORKS (https://arxiv.org/pdf/1711.11293.pdf)
A novel data augmentation method based on Cycle-GAN, and a new offline handwritten signature verification system based on CapsNet.
This repository contains the code for the paper "Self-supervised Text Style Transfer using Cycle-Consistent Adversarial Networks".
Generative Adversarial Networks (GANs) for 3D MRI images [for deepBrainHackMTL-2017]
Official Implementation for the paper Deep Domain Adaptation: A Sim2Real Neural Approach for Improving Eye-Tracking System.
This repository is about different types of GANs in pytorch, their proper settings and training results
Object Detection in Twilight
🖼️ Our CycleGAN Implementation for Image-to-Image Translation project leverages PyTorch to seamlessly transform images between domains, all without paired examples. With a keen focus on innovation and effectiveness, we've explored CycleGAN's capabilities across various domains. Join us as we delve into the world of image translation technology! 🚀
This is a PyTorch implementation of Cycle GAN from Scratch.
Image to image translation using CycleGAN for transforming photographs into Monet style paintings
Attention based Single Image Dehazing Using Improved CycleGAN
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