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Image Stylization
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Image stylization is a task that involves transforming an input image into a new image that has a different style, while preserving the content of the original image. The goal of image stylization is to create visually appealing images with a specific style or aesthetic, such as impressionism, cubism, or surrealism. It can also be used to make images more visually appealing for specific applications, such as social media or advertising.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Net-Mist/style-transfer-tf2
Instance Normalization: The Missing Ingredient for Fast Stylization
https://github.com/S-aiueo32/srntt-pytorch
https://github.com/Tonyhuiii/color-transform
https://github.com/Uemuet/style-transfer
https://github.com/Uemuet/styletransfer-adaptive
https://github.com/afruehstueck/tileGAN
https://github.com/aryan-mann/style-transfer
Instance Normalization: The Missing Ingredient for Fast Stylization
https://github.com/brightyoun/Video-Style-Transfer
Instance Normalization: The Missing Ingredient for Fast Stylization
https://github.com/buddly27/stylish
Instance Normalization: The Missing Ingredient for Fast Stylization
https://github.com/clovaai/WCT2
https://github.com/cristinecosta/CompVis
https://github.com/cryu854/FastStyle
Instance Normalization: The Missing Ingredient for Fast Stylization
https://github.com/cryu854/SinGAN
Instance Normalization: The Missing Ingredient for Fast Stylization
https://github.com/deepdeepdot/FastPhotoStyle
https://github.com/etttttte/mayfest2018
Instance Normalization: The Missing Ingredient for Fast Stylization
https://github.com/freedombenLiu/FastPhotoStyle
https://github.com/guizilaile23/ZSL-SSS
https://github.com/gunpowder1473/Adaptive-Style-Transfer-Tensorflow
https://github.com/hollygrimm/cyclegan-keras-art-attrs
Instance Normalization: The Missing Ingredient for Fast Stylization
https://github.com/jcjohnson/fast-neural-style
Instance Normalization: The Missing Ingredient for Fast Stylization
https://github.com/labmlai/annotated_deep_learning_paper_implementations
Instance Normalization: The Missing Ingredient for Fast Stylization
https://github.com/lengstrom/fast-style-transfer
Instance Normalization: The Missing Ingredient for Fast Stylization
https://github.com/midm/FastPhotoStyle
https://github.com/milmor/perceptual-losses-neural-style
Instance Normalization: The Missing Ingredient for Fast Stylization
https://github.com/mousecpn/Domain-Generalization-via-Image-Stylization
Frustratingly Simple Domain Generalization via Image Stylization
https://github.com/oist/psgan
Copy the Old or Paint Anew? An Adversarial Framework for (non-) Parametric Image Stylization
https://github.com/riven314/PerceptualLoss-FastAI
Instance Normalization: The Missing Ingredient for Fast Stylization
https://github.com/salesforce/doodl
EDICT: Exact Diffusion Inversion via Coupled Transformations
https://github.com/samwatts98/Fast-Neural-Style-Transfer-with-Laplacian-Loss-TensorFlow-1.13
Instance Normalization: The Missing Ingredient for Fast Stylization
https://github.com/sleebapaul/AuriaKathi
https://github.com/smaranjitghose/DeepHoli
https://github.com/sukkritsharmaofficial/NEURALFUSE
https://github.com/sundogai/style-transfer
Instance Normalization: The Missing Ingredient for Fast Stylization
https://github.com/svjack/PhotoWCT
https://github.com/tbullmann/imagetranslation-tensorflow
Instance Normalization: The Missing Ingredient for Fast Stylization
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.