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 91–100 of 124 papers

TitleStatusHype
Unsupervised Multi-Domain Image Translation with Domain-Specific Encoders/Decoders—0
Unsupervised one-to-many image translation—0
Variational Bayesian Framework for Advanced Image Generation with Domain-Related Variables—0
XOGAN: One-to-Many Unsupervised Image-to-Image Translation—0
Instance-aware Image-to-Image TranslationCode0
InstaGAN: Instance-aware Image-to-Image TranslationCode0
Unsupervised Image-to-Image Translation with Self-Attention NetworksCode0
In2I : Unsupervised Multi-Image-to-Image Translation Using Generative Adversarial NetworksCode0
Improving Shape Deformation in Unsupervised Image-to-Image TranslationCode0
High-Resolution Daytime Translation Without Domain LabelsCode0
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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