patchgan 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。
This Repository Contains Solution to the Assignments of the Generative Adversarial Networks (GANs) Specialization from deeplearning.ai on Coursera Taught by Sharon Zhou, Eda Zhou, Eric Zelikman
Progressive Image Inpainting (Kolmogorov Team solution for Huawei Hackathon 2019 summer)
Redesigning the Pix2Pix model for small datasets with fewer parameters and different PatchGAN architecture
✨ Dive into image denoising magic! This project uses Attention U-Net and PatchGAN to tackle noise types like low Gaussian and salt-and-pepper noise. Perfect for computer vision, deep learning, and generative modeling enthusiasts. Restore clarity to noisy images with cutting-edge AI! 🚀🎨
Colorizing Black & White images using GAN
Using Pix2Pix GAN for translating Anime images to something more aesthetic
Generate Faces Using Deep Convolutional Generative Adversarial Networks (DCGAN)
A PyTorch-based image synthesis and computer vision framework.
Sketch-to-Image Criminal Identification System using a pix2pix GAN trained on the CUHK dataset to generate realistic images from sketches. A classifier is then trained on mugshot data to identify individuals based on generated images, enhancing forensic sketch recognition with deep learning for accurate identification.
A PyTorch implementation of the Pix2Pix model (cGAN) for image-to-image translation. This project translates semantic segmentation maps to photorealistic images using the Cityscapes dataset.
horse2zebra
An end2end PyTorch CycleGAN framework for unpaired facial age translation, with full training pipeline, AWS/S3 utilities, and an interactive Gradio demo.
An Image colorization algorithm using PatchGan and Convolution Block Attention Modules (CBAM)
Face Aging & De-Aging using CycleGAN, PyTorch, OpenCV and Gradio. AI-powered facial age transformation with an interactive web interface.
该框架旨在从 CT 数据生成 18F-FDG PET 图像，从而促进肺癌的准确定位。该流程集成了使用 YOLOv11 的 FOV 校正、通过 CPGAN 生成合成 18F-FDG PET、ROI 裁剪、使用 SegResNet 的肿瘤分割，以及最终的 PET-CT 融合，以增强肿瘤可视化。
Analysis of different models for mobile ocular biometrics.
Colorizing grayscale facial images using a U-Net neural network architecture with Patch GAN
Implementing and comparing CGAN and WGAN-GP for grayscale image colorization using U-Net and PatchGAN in L*a*b color space, with experiments on ImageNet and MS-COCO.
Pix2Pix GAN for brain hemorrhage segmentation on ~318 CT scans. U-Net generator + PatchGAN discriminator, reaching 0.72 Dice, 0.57 IoU, 0.80 sensitivity and 0.87 specificity.
Generating Maps from Satellite images using the Pix2Pix GAN.