https://github.com/winfried-loetzsch/wise
Style Transfer by Relaxed Optimal Transport and Self-Similarity
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/wkhademi/ImageEnhancement
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/wkostuch/wild-style
https://github.com/woctezuma/stylegan2-projecting-images
Image2StyleGAN: How to Embed Images Into the StyleGAN Latent Space?
https://github.com/wonbeomjang/cyclegan-pytorch
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/woodrush/neural-art-tf
https://github.com/xhujoy/CycleGAN-tensorflow
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/xidexia/realtime_PST
Joint Bilateral Learning for Real-time Universal Photorealistic Style Transfer
https://github.com/xinyuanc91/Gated-GAN
Gated-GAN: Adversarial Gated Networks for Multi-Collection Style Transfer
https://github.com/xiuyu0000/papers_with_examples/tree/main/arbitrary_image_stylization
Exploring the structure of a real-time, arbitrary neural artistic stylization network
https://github.com/xiuyu0000/papers_with_examples/tree/main/cyclegan
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/xiuyu0000/papers_with_examples/tree/main/reconet
https://github.com/xuberance137/styleflow
https://github.com/xuduo35/MakeLongVideo
Tune-A-Video: One-Shot Tuning of Image Diffusion Models for Text-to-Video Generation
https://github.com/xw-hu/Mask-ShadowGAN
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/xxlya/CycleGAN
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/xxxNARUTO228xxx/Neural-Style-Transfer-Gatys-LapStyle
https://github.com/yakhyo/Fast-Neural-Style-Transfer
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
https://github.com/yanggeng1995/vae_tacotron
Learning latent representations for style control and transfer in end-to-end speech synthesis
https://github.com/yangyucheng000/CycleGan
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/yangyucheng000/Paper-2/tree/main/WS-VAD-mindspore-main
https://github.com/yangyucheng000/Pix2pix-2
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/yangyucheng000/ReCoNet
https://github.com/yangyucheng000/arbitrary_image_stylization
Exploring the structure of a real-time, arbitrary neural artistic stylization network
https://github.com/yangyucheng000/ascend_ArbitraryStyleTransfer
Exploring the structure of a real-time, arbitrary neural artistic stylization network
https://github.com/yardenfren1996/B-LoRA
https://github.com/yaswanthpalaghat/Implementing-Neural-Style-Transfer
https://github.com/ycjing/Character-Stylization
https://github.com/yesidc/ProjectANNsWTF
https://github.com/yex666/cyclegan-in-mindspore
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/yjunej/AdaIN-tf2
Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization
https://github.com/ykasten/layered-neural-atlases
https://github.com/yky138495/awesome-matlab-rank-1000
https://github.com/yotharit/image_style_transfer
https://github.com/yujiachen-y/StyleBank
StyleBank: An Explicit Representation for Neural Image Style Transfer
https://github.com/yulunzhang/MST
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.