Papers with Code 아카이브
Unsupervised Image-To-Image Translation
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Unsupervised image-to-image translation is the task of doing image-to-image translation without ground truth image-to-image pairings.
<span style="color:grey; opacity: 0.6">( Image credit: Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/kunheek/style-aware-discriminator
공식 코드A Style-aware Discriminator for Controllable Image Translation
https://github.com/linjx-ustc1106/TuiGAN-PyTorch
공식 코드TuiGAN: Learning Versatile Image-to-Image Translation with Two Unpaired Images
https://github.com/mid-push/irwgan
공식 코드Unaligned Image-to-Image Translation by Learning to Reweight
https://github.com/mingyuliutw/UNIT
공식 코드https://github.com/nvlabs/MUNIT
공식 코드https://github.com/nvlabs/imaginaire
공식 코드COCO-FUNIT: Few-Shot Unsupervised Image Translation with a Content Conditioned Style Encoder
https://github.com/qiangwang57/coreg_flim_histology
공식 코드https://github.com/rajiv1990/Unsupervised-Cross-domain-I2I-using-a-Shared-Discriminator
공식 코드Learning Unsupervised Cross-domain Image-to-Image Translation Using a Shared Discriminator
https://github.com/rmokady/structural-analogy
공식 코드https://github.com/royorel/FFHQ-Aging-Dataset
공식 코드https://github.com/royorel/Lifespan_Age_Transformation_Synthesis
공식 코드https://github.com/sagiebenaim/DistanceGAN
공식 코드https://github.com/sagiebenaim/OneShotTranslation
공식 코드https://github.com/sagiebenaim/gan_bound
공식 코드Estimating the Success of Unsupervised Image to Image Translation
https://github.com/saic-mdal/HiDT
공식 코드https://github.com/sangwoomo/instagan
공식 코드https://github.com/smerdov/CS_GO_Sensors_Data_Analysis
공식 코드AI-enabled Prediction of eSports Player Performance Using the Data from Heterogeneous Sensors
https://github.com/smerdov/eSports_Sensors_Dataset
공식 코드https://github.com/smerdov/smart_chair_client
공식 코드https://github.com/taki0112/UGATIT
공식 코드https://github.com/ubc-vision/lsenerf
공식 코드LSE-NeRF: Learning Sensor Modeling Errors for Deblured Neural Radiance Fields with RGB-Event Stereo
https://github.com/vishwa91/deepir
공식 코드https://github.com/williamyang1991/gp-unit
공식 코드Unsupervised Image-to-Image Translation with Generative Prior
https://github.com/xianggao1102/learning-to-incorporate-texture-saliency-adaptive-attention-to-image-cartoonization
공식 코드Learning to Incorporate Texture Saliency Adaptive Attention to Image Cartoonization
https://github.com/yhlleo/DWC-GAN
공식 코드Describe What to Change: A Text-guided Unsupervised Image-to-Image Translation Approach
https://github.com/yhlleo/GMM-UNIT
공식 코드https://github.com/znxlwm/UGATIT-pytorch
공식 코드https://github.com/2023-MindSpore-1/ms-code-134
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/2023-MindSpore-1/ms-code-158
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/2023-MindSpore-1/ms-code-184
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/U-GAT-IT
https://github.com/2023-MindSpore-1/ms-code-7/tree/main/U-GAT-IT
https://github.com/AbhinavTalari/Night2Day
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/Adi-iitd/AI-Art
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/AlphaKong/CycleGAN
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.