SOTAVerified

Unsupervised Image-To-Image Translation

Unsupervised image-to-image translation is the task of doing image-to-image translation without ground truth image-to-image pairings.

( Image credit: Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 71–80 of 124 papers

TitleStatusHype
Medical Image Generation using Generative Adversarial Networks—0
Adversarial Wear and Tear: Exploiting Natural Damage for Generating Physical-World Adversarial Examples—0
A Framework for Generalizing Critical Heat Flux Detection Models Using Unsupervised Image-to-Image Translation—0
Unsupervised Many-to-Many Image-to-Image Translation Across Multiple Domains—0
Closing the Reality Gap with Unsupervised Sim-to-Real Image Translation—0
Combining Noise-to-Image and Image-to-Image GANs: Brain MR Image Augmentation for Tumor Detection—0
Contrastive Learning for Unsupervised Image-to-Image Translation—0
Crossing-Domain Generative Adversarial Networks for Unsupervised Multi-Domain Image-to-Image Translation—0
Dense Multitask Learning to Reconfigure Comics—0
Disentangled Unsupervised Image Translation via Restricted Information Flow—0
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All datasetsSVNH-to-MNISTFreiburg Forest Dataset

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CyCADA pixel+featClassification Accuracy90.4—Unverified
2DTNClassification Accuracy84.4—Unverified
3ADDAClassification Accuracy76—Unverified
4DANNClassification Accuracy73.6—Unverified
#ModelMetricClaimedVerifiedStatus
1In2IPSNR21.65—Unverified
2cycGANPSNR18.57—Unverified
3UNITPSNR9.42—Unverified