Redesigning the Pix2Pix model for small datasets with fewer parameters and different PatchGAN architecture
-
Updated
Oct 18, 2025 - Python
Redesigning the Pix2Pix model for small datasets with fewer parameters and different PatchGAN architecture
Using Pix2Pix GAN for translating Anime images to something more aesthetic
AquaThreat is a research-driven AI project focused on underwater image enhancement and naval security applications, particularly detecting and analyzing threats such as underwater mines. It integrates advanced deep learning architectures like GANs, PatchGAN, and U-Nets to improve visibility in challenging aquatic environments.
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.
Face Aging & De-Aging using CycleGAN, PyTorch, OpenCV and Gradio. AI-powered facial age transformation with an interactive web interface.
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.
Colorizing grayscale facial images using a U-Net neural network architecture with Patch GAN
Analysis of different models for mobile ocular biometrics.
DCGAN trained on CelebA to generate 64×64 face images from scratch using PyTorch — with Comet ML experiment tracking
Task: Neural Style Transfer. The implemented solution uses a CycleGan architecture.
Bidirectional face age transformation (young↔old) with conditional CycleGAN — AdaIN, multi-scale discriminator, VGG perceptual loss, W&B tracking on RTX 6000 Ada
Project based on Neural Style Transfer, implemented using a CycleGan architecture
Unpaired Image-to-Image Translation using CycleGANs (horse2zebra)
Add a description, image, and links to the patchgan topic page so that developers can more easily learn about it.
To associate your repository with the patchgan topic, visit your repo's landing page and select "manage topics."