《GANs in Action: Deep learning with Generative Adversarial Networks》的配套仓库
cycle-gan 开源项目推荐(80 个)
cycle-gan 话题在 GitHub 上没有填写简介,这里按 Star 数汇总最相关的热门仓库。
热门项目 前 20
按 Star 数排序展示前 20 个 · GitHub 共 80 个仓库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
该项目在 GitHub 上没有填写描述
Hands-On Deep Learning Algorithms with Python, By Packt
Voice Conversion using Cycle GAN's For Non-Parallel Data
PyTorch 实现了论文《零样草图图像检索的语义绑定配对循环一致性》,CVPR 2019。
Translating Synthetic RIRs to Real RIRs
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/)
Pixel-level domain adaptation: A study case on generating parking-slot image samples.
Attention based Single Image Dehazing Using Improved CycleGAN
This repo contains various use-cases of deep-learning implemented in Pytorch. It also contains summarized notes of each chapter from the book, 'Deep Learning' written by Ian Goodfellow.
writing style transfer using cycle gan
Reproducing PARALLEL-DATA-FREE VOICE CONVERSION USING CYCLE-CONSISTENT ADVERSARIAL NETWORKS (https://arxiv.org/pdf/1711.11293.pdf)
Official Implementation for the paper Deep Domain Adaptation: A Sim2Real Neural Approach for Improving Eye-Tracking System.
AI-enabled Interior decoration, powered by CycleGANs. Built for @NextTechLabAP's #9Hacks!
Pytorch implementation of Self Attentive Adversarial Stain Normalization (SAASN).
This repository is about different types of GANs in pytorch, their proper settings and training results
A novel data augmentation method based on Cycle-GAN, and a new offline handwritten signature verification system based on CapsNet.
Clean your docs!
关于这个话题
- 清单取自 GitHub 话题页并按 Star 数排序,每次展示前 20 个项目;原始页面见 https://github.com/topics/cycle-gan。
- 该话题在 GitHub 上共有 80 个仓库, 本站收录的是其中最热门的 20 个,不是全量列表。
- Star / Fork 每日自动刷新一次,实时数据以 GitHub 为准。
- 当前 20 个项目累计 2571 Star,覆盖 3 种主要语言,数据更新于 2026-11-08。
- 中文介绍来自 GitHub 官方话题说明(github/explore)的机器翻译,可点「查看原文」对照;译文缺失时会先展示原文。