[CVIU2023] Codes for my paper "SSDA-YOLO: Semi-supervised Domain Adaptive YOLO for Cross-Domain Object Detection"
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Updated
Apr 22, 2023 - Python
[CVIU2023] Codes for my paper "SSDA-YOLO: Semi-supervised Domain Adaptive YOLO for Cross-Domain Object Detection"
Official PyTorch implementation of QuantArt (CVPR2023)
<케라스 창시자에게 배우는 딥러닝 2판> 도서의 코드 저장소
PyTorch implementation of "Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization"
Implementation from scratch of [Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization [Huang+, ICCV2017]]
Combine two images and produce new image with style of first image and content of second image
A clear and lucid implementation of Instance Aware Tanslation in Image Style Transfer using GANs
PyTorch implementation of "A Learned Representation For Artistic Style"
Easy machine learning in PHP by leveraging the power of TensorFlow
Convert an image into a nice-looking Voronoi diagram using one of many available techniques with options for customization.
A macOS Swift Playground for testing your image stylizing CoreML model
PyTorch implementation of Gatys et al., 2016 from scratch
Dissertation Project based on Image Style Transfer. Created a user interactive graphics editor that allows users to create masks to control the region where the algorithm will effect.
To realize image style transfer using basic components of neural network
InstantID : Zero-shot Identity-Preserving Generation in Seconds | RunPod Serverless Worker
Artify is an AI-powered image style transfer bot that transforms ordinary photos into stunning artworks inspired by famous artists, from classical masters to modern visionaries.
Fei Gao's Homepage
In this study, we work to transfer the pattern to the basic face image from the pattern face image, by adjusting the latent space and moving within it.
Flask-based web app that performs Neural Style Transfer (NST) using TensorFlow Hub. It allows users to upload a content image and a style image, processes them, and returns the stylized image.
Add a description, image, and links to the image-style-transfer topic page so that developers can more easily learn about it.
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