https://github.com/T-C-J/shuiying
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/TAMU-VITA/AGD
GAN Slimming: All-in-One GAN Compression by A Unified Optimization Framework
https://github.com/TJJTJJTJJ/pytorch_CycleGAN_frame
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/TanguyJeanneau/white-mirror
https://github.com/Taoudi/Monet-ization-of-Images
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/Tee0125/pytorch-fast-style-transfer
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
https://github.com/TheConfused1/Real-time-neural-style-transfer
https://github.com/Tiannia/intro_to_ai
https://github.com/TianxiangMa/MUST-GAN
MUST-GAN: Multi-level Statistics Transfer for Self-driven Person Image Generation
https://github.com/Tonyhuiii/color-transform
https://github.com/Trustworthy-AI-Group/TransferAttack
Improving the Transferability of Adversarial Examples with Arbitrary Style Transfer
https://github.com/UdbhavPrasad072300/Generate-Fake-Faces-with-CVAE-in-PyTorch
https://github.com/Uemuet/style-transfer
https://github.com/Uemuet/styletransfer-adaptive
https://github.com/VAShibaev/text_style_transfer
Style Transfer for Texts: Retrain, Report Errors, Compare with Rewrites
https://github.com/VadimFarutin/neural-style-transfer
https://github.com/Vaibhavck/Style-Transfer-VGG19
https://github.com/Varunittigi/Neural-Style-transfer
https://github.com/VedantDere0104/Cycle_GAN
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/VegB/VLN-Transformer
Multimodal Text Style Transfer for Outdoor Vision-and-Language Navigation
https://github.com/Vill-Lab/forkOfStyleShot
https://github.com/VinceMarron/style_transfer
https://github.com/Vinr1ch/cs390-lab2
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
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
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
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.