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/Cardio-AI/detcyclegan_pytorch
공식 코드https://github.com/DavidAbramian/refacing
공식 코드Refacing: reconstructing anonymized facial features using GANs
https://github.com/Elvinky/IEGAN
공식 코드Independent Encoder for Deep Hierarchical Unsupervised Image-to-Image Translation
https://github.com/GeorgeEskandar/USIS-Unsupervised-Semantic-Image-Synthesis
공식 코드https://github.com/Ha0Tang/AttentionGAN
공식 코드Attention-Guided Generative Adversarial Networks for Unsupervised Image-to-Image Translation
https://github.com/HideUnderBush/UI2I_via_StyleGAN2
공식 코드Unsupervised Image-to-Image Translation via Pre-trained StyleGAN2 Network
https://github.com/Hindawi91/Pseudo_Supervised_Metrics
공식 코드https://github.com/IVRL/ComicsDepth
공식 코드https://github.com/JunlinHan/CWR
공식 코드https://github.com/JunlinHan/DCLGAN
공식 코드Dual Contrastive Learning for Unsupervised Image-to-Image Translation
https://github.com/KU-CVLAB/LANIT
공식 코드LANIT: Language-Driven Image-to-Image Translation for Unlabeled Data
https://github.com/LCAD-UFES/publications-arruda-ijcnn-2019
공식 코드Cross-Domain Car Detection Using Unsupervised Image-to-Image Translation: From Day to Night
https://github.com/MInner/lrmf
공식 코드Log-Likelihood Ratio Minimizing Flows: Towards Robust and Quantifiable Neural Distribution Alignment
https://github.com/NVlabs/FUNIT
공식 코드https://github.com/NetEase-GameAI/SPatchGAN
공식 코드SPatchGAN: A Statistical Feature Based Discriminator for Unsupervised Image-to-Image Translation
https://github.com/Onr/Council-GAN
공식 코드https://github.com/YangNaruto/FQ-GAN
공식 코드https://github.com/alpc91/NICE-GAN-pytorch
공식 코드Reusing Discriminators for Encoding: Towards Unsupervised Image-to-Image Translation
https://github.com/anonymous-ai-for-earth/satellite-to-satellite-translation
공식 코드https://github.com/avivga/lord
공식 코드https://github.com/brownvc/ganimorph
공식 코드Improving Shape Deformation in Unsupervised Image-to-Image Translation
https://github.com/carolineec/informative-drawings
공식 코드Learning to generate line drawings that convey geometry and semantics
https://github.com/clovaai/tunit
공식 코드Rethinking the Truly Unsupervised Image-to-Image Translation
https://github.com/cyq373/ZUNIT
공식 코드https://github.com/dbash/pix2pix_cyclegan_guess_noise
공식 코드https://github.com/dreamtalecore/scs-uit
공식 코드Separating Content and Style for Unsupervised Image-to-Image Translation
https://github.com/eitanrich/lin-im2im
공식 코드The Surprising Effectiveness of Linear Unsupervised Image-to-Image Translation
https://github.com/ekcole/unsupGAN-release
공식 코드Unsupervised MRI Reconstruction with Generative Adversarial Networks
https://github.com/georghess/neurad-studio
공식 코드https://github.com/hindawi91/dips
공식 코드https://github.com/itsss/img2img_sa
공식 코드Unsupervised Image-to-Image Translation with Self-Attention Networks
https://github.com/jampang41/cst-s3d
공식 코드https://github.com/jhoffman/cycada_release
공식 코드https://github.com/junyanz/CycleGAN
공식 코드Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix
공식 코드Unpaired 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.