Generating aerial flood prediction imagery with generative adversarial networks
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Updated
Jun 29, 2024 - Python
Generating aerial flood prediction imagery with generative adversarial networks
[CVPR 2020] GAN Compression: Efficient Architectures for Interactive Conditional GANs
PaddlePaddle GAN library, including lots of interesting applications like First-Order motion transfer, Wav2Lip, picture repair, image editing, photo2cartoon, image style transfer, GPEN, and so on.
DeepNude's algorithm and general image generation theory and practice research, including pix2pix, CycleGAN, UGATIT, DCGAN, SinGAN, ALAE, mGANprior, StarGAN-v2 and VAE models (TensorFlow2 implementation). DeepNude的算法以及通用生成对抗网络(GAN,Generative Adversarial Network)图像生成的理论与实践研究。
Image-to-Image Translation in PyTorch
Generate your own Star Wars 🚀🌟 Lego figures from your favorite images using AI. 🎨🤖
Utilize a MobileNetV2 encoder and Pix2Pix decoder to perform precise semantic segmentation, distinguishing objects in images, such as identifying flooded areas in flood images. The purpose is to enable accurate object delineation for applications like disaster response and environmental monitoring.
A project to colourize gray scale photo using generative adversial network (GAN)
The repository for the Tallahassee, FL crime map project using GAN.
Links to my works, where a variety of generative models are implemented using TensorFlow and PyTorch. Among the implemented models are Autoencoder, VAE, GAN, Pix2Pix, among others.
This repository contains the GAN programs that we implemented for the TCIRRP dataset as part of mini project in university.
Repository for the "Machine Learning for the Web" class at ITP, NYU
Entries for the 2023 5th National College Student Integrated Circuit EDA Elite Challenge. SoC chip physical layout static IR drop prediction project based on methods such as image processing and NLP unsupervised learning.
Pix2Pix and CycleGAN training code
[ICCV 2019] Guided Image-to-Image Translation with Bi-Directional Feature Transformation
Research project aiming to collect a dataset of paired fog images and apply the pix2pix model to it, conducted at the University of Utah
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