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34 search results found

Paper Implementations ⭐ 598

Use PyTorch to implement some classic frameworks

Stylized Imagenet ⭐ 485

Code to create Stylized-ImageNet, a stylized version of standard ImageNet (ICLR 2019 Oral)

Cartoonify ⭐ 313

Deploy and scale serverless machine learning app - in 4 steps.

PyTorch (and PyTorch Lightning) implementation of Neural Style Transfer, Pix2Pix, CycleGAN, and Deep Dream!

Awesome Segment Anything Extensions ⭐ 255

Segment-anything related awesome extensions/projects/repos.

Style_transfer ⭐ 212

CNN image style transfer 🎨.

Sketch To Art ⭐ 160

🖼 Create artwork from your casual sketch with GAN and style transfer

Deformable Style Transfer (ECCV 2020)

Frostnet ⭐ 86

FrostNet: Towards Quantization-Aware Network Architecture Search

Brushstroke Parameterized Style Transfer ⭐ 58

Code for our CVPR 2021 Paper "Rethinking Style Transfer: From Pixels to Parameterized Brushstrokes".

Deep Transfer ⭐ 53

PyTorch implementation of "Universal Style Transfer via Feature Trasforms"

PyTorch/Tensorflow solutions for Stanford's CS231n: "CNNs for Visual Recognition"

Chinese Character And Calligraphic Image Processing ⭐ 28

Some interesting method like style transfer, GAN, deep neural networks for Chinese character and calligraphic image processing

Stylizeapp ⭐ 27

A flask website for style transfer

Style Transfer ⭐ 24

Style transfer in TensorFlow with color preservation

🎨 Poor Man's Style Transfer - Painting an image with the style of another, without machine learning

Official Implementation of ArtNeRF: A Stylized Neural Implicit Representation for 3D-Aware Cartoonized Face Synthesis

Py Style Transfer ⭐ 20

🎨 Artistic neural style transfer with tweaks (pytorch).

Photorealistic Style Transfer ⭐ 19

Based on the paper 'High-Resolution Network for Photorealistic Style Transfer' I provide a PyTorch implementation of the model. https://github.com/limingcv/Photorealistic-Style-T

Neural Style Transfer ⭐ 19

Neural Style Transfer

Styletransfer Pytorch ⭐ 14

Implementation of image style transfer in PyTorch

A deep learning library with static computational graph and auto-diff in C++.

Computervision ⭐ 13

Implementations of algorithms and operations used in Computer Vision: solely for Neural style transfer.

Artistia ⭐ 12

A unified ML platform for Image Transformation (style transfer, image colorization, sketching and pixelating)

Face Preserving Style Transfer ⭐ 9

Fast style transfer with facial preservation. Final project for CSCI-GA.2271: Computer Vision (Fall 2018) at New York University.

Line Art Colorization Spade ⭐ 9

SPADE-based Line Art Colorization

Fast Style Transfer ⭐ 7

Convert any photos or videos to artwork. Implementation of Style Transfer in TensorFlow.

Neural Artistic Style Transfer ⭐ 6

A unique deep learning technique is used to create artistic images by separating and recombining the content and style of arbitrary images. The style of an image is transferred to the content image. These visual effects are implemented using the Convolutional Neural Networks.

Pytorch_fast_style_transfer ⭐ 6

Pytorch implementent of the fast style transfer paper "Perceptual Losses for Real-Time Style Transfer and Super-Resolution".

3d_conceptal_design_using_deep_learning ⭐ 6

Sold in Amazon as Textbook 🔛 Springer Lecture Note Series "Advances in Computer Science" 🔛 2019 IEEE Computer Vision Conference

Neural Style ⭐ 6

TensorFlow implementations of art style transfer, such as Neural Style.

Style transfer using WCT transforms

Styletransferwithcatalyst ⭐ 5

This repository shows style transfer in realtime experiment with catalyst deep learning framework

Neural Network Zoo ⭐ 5

🧠🕸️ Neural network architectures implemented in PyTorch for educational purposes.

Neural Style Transfer ⭐ 5

Neural Style Transfer Algorithm

Interactive Cloth Segmentation With Saliency Guided Style Transfer ⭐ 5

A framework to quickly generate high-quality stylized clothing from style images. The framework gives users the option to stylize only selected components. It uses Saliency guided style transfer to generate high-quality outputs.

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