https://github.com/YoungWoong-Cho/Decay
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
Papers with Code 아카이브
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
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
https://github.com/Zhachory1/MusicNST
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
https://github.com/abhishtagatya/paintgan
https://github.com/abhiskk/fast-neural-style
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
https://github.com/aboev/arae-tf
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
https://github.com/ahmedbesbes/cycle-gan
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/ahmedoumar/Neural_style_transfer_keras
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
https://github.com/aigagror/discriminator-style-transfer
https://github.com/aijialin/style_transfer
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
https://github.com/aitorzip/PyTorch-CycleGAN
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/ajit2704/peexle
https://github.com/akanametov/NeuralStyleTransfer
https://github.com/akanametov/neural-style-transfer
https://github.com/akashrajkn/micaugment
https://github.com/akshayb7/Style-Transfer
https://github.com/alexanderivanov2424/CSCI-1430-Final-Project
https://github.com/alexis-jacq/Pytorch-Tutorials
https://github.com/alexjc/neural-enhance
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
https://github.com/alexquach/cycleGAN
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/algonomicon/a-neural-algorithm-of-artistic-style
https://github.com/ali-vilab/VGen
Composer: Creative and Controllable Image Synthesis with Composable Conditions
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.