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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/VyshnaviSK/Face2Mask-CycleGAN

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/WalterJohnson0/tf-keras-implementation-of-Image-Style-transformation-network

Perceptual Losses for Real-Time Style Transfer and Super-Resolution

https://github.com/WeiYangze/hibernate-demo

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/Wenchao-Du/LIR-for-Unsupervised-IR

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/Westlake-AI/openmixup

AlignMixup: Improving Representations By Interpolating Aligned Features

https://github.com/WhiskyChoy/language-style-transfer

Style Transfer from Non-Parallel Text by Cross-Alignment

https://github.com/XiSHEN0220/SegSwap

Learning Co-segmentation by Segment Swapping for Retrieval and Discovery

https://github.com/XiangGao1102/CTSS

Learning to Incorporate Texture Saliency Adaptive Attention to Image Cartoonization

https://github.com/YCJGG/Muti-style-transfer-by-camera

Universal Style Transfer via Feature Transforms

https://github.com/Yingqiancui/FT-Shield

FT-Shield: A Watermark Against Unauthorized Fine-tuning in Text-to-Image Diffusion Models

https://github.com/YiteWang/CS547-final-project

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/YouYueHuang/CycleGAN_Unsupervised_Domain_Adaptation

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/Yougunhee/cycleGAN

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/YoungWoong-Cho/Decay

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/ZC119/Handwritten-CycleGAN

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/ZVK/Talking-Heads

Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization

https://github.com/ZVK/talking_heads

Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization

https://github.com/Zekromaegis/Neural-Style-Transfer

A Neural Algorithm of Artistic Style

https://github.com/Zhachory1/MusicNST

A Neural Algorithm of Artistic Style

https://github.com/ZhangGongjie/CycleGAN-Pytorch

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/ZyoungXu/MoSt-DSA

Perceptual Losses for Real-Time Style Transfer and Super-Resolution

https://github.com/aadhithya/AdaIN-pytorch

Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization

https://github.com/abhijeetmittal/Convolutional-Neural-Network

A Neural Algorithm of Artistic Style

https://github.com/abhishtagatya/paintgan

A Neural Algorithm of Artistic Style

https://github.com/abhiskk/fast-neural-style

Perceptual Losses for Real-Time Style Transfer and Super-Resolution

https://github.com/aboev/arae-tf

Adversarially Regularized Autoencoders

https://github.com/acetylSv/GST-tacotron

Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis

https://github.com/acht7111020/DSMAP

Domain-Specific Mappings for Generative Adversarial Style Transfer

https://github.com/adnanalam53/cycleGAN

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/afruehstueck/tileGAN

TileGAN: Synthesis of Large-Scale Non-Homogeneous Textures

https://github.com/ahmedbesbes/cycle-gan

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/ahmedoumar/Neural_style_transfer_keras

A Neural Algorithm of Artistic Style

https://github.com/ahmedsalahacc/Image-Style-Transfer-with-Cycle-GAN

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/ai-forever/ru-gpts

Methods for Detoxification of Texts for the Russian Language

https://github.com/ai-unicamp/tts-objective-metrics

Mellotron: Multispeaker expressive voice synthesis by conditioning on rhythm, pitch and global style tokens

https://github.com/aigagror/discriminator-style-transfer

Style is a Distribution of Features

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.