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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! 🚀🎨
Using Pix2Pix GAN for translating Anime images to something more aesthetic
Generate Faces Using Deep Convolutional Generative Adversarial Networks (DCGAN)
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.
An Image colorization algorithm using PatchGan and Convolution Block Attention Modules (CBAM)
Task: Neural Style Transfer. The implemented solution uses a CycleGan architecture.
Generating Maps from Satellite images using the Pix2Pix GAN.
This repo is about an image enhancement project using GANs with Deep Residual U Net and Patch wise discriminator
Project based on Neural Style Transfer, implemented using a CycleGan architecture
This project explores and implements a state-of-the-art approach for automatic image recolorization using Conditional Generative Adversarial Networks (cGANs).
Analysis of different models for mobile ocular biometrics.