Awesome 3D Stylization - Advances in 3D Neural Stylization
-
Updated
Jun 26, 2024
Awesome 3D Stylization - Advances in 3D Neural Stylization
This Streamlit app demonstrates neural style transfer, a technique for combining the content of one image with the style of another using a convolutional neural network (CNN).
Here are all my code files of Advanced AI/ML architectures built from scratch using Pytorch.
MetaStyle: Three-Way Trade-Off Among Speed, Flexibility, and Quality in Neural Style Transfer
Fitstyle is an app that allows users to merge photos and art to create styled images.
Fitstyle is an app that allows users to merge photos and art to create styled images.
Task: Neural Style Transfer. The implemented solution uses a CycleGan architecture.
AI Makerspace: Blueprints for developing machine learning applications with state-of-the-art technologies.
This project consists of a web application built with React for the frontend and Flask for the backend. The application allows users to perform neural style transfer on images, where the style of one image is applied to the content of another image to generate visually appealing results.
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.
Project page for StyleCity: Large-Scale 3D Urban Scenes Stylization with Vision-and-Text Reference via Progressive Optimization
Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Network…
VGG19 --> Neural Style Transfer
Fast Neural Style Transfer implementation using PyTorch
Code and data release for ICCP 2022 paper "Time-of-Day Neural Style Transfer for Architectural Photographs".
Image Processing using MatLab and TensorFlow
Learning to Generalize towards Unseen Domains via a Content-Aware Style Invariant Framework for Disease Detection from Chest X-rays
Labs for Generative Deep Learning with TensorFlow by DeepLearning.AI on Coursera
Add a description, image, and links to the neural-style-transfer topic page so that developers can more easily learn about it.
To associate your repository with the neural-style-transfer topic, visit your repo's landing page and select "manage topics."