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 81–90 of 124 papers

TitleStatusHype
Enhanced Unsupervised Image-to-Image Translation Using Contrastive Learning and Histogram of Oriented Gradients—0
Exemplar Guided Unsupervised Image-to-Image Translation with Semantic Consistency—0
Federated Contrastive Learning for Privacy-Preserving Unpaired Image-to-Image Translation—0
Federated CycleGAN for Privacy-Preserving Image-to-Image Translation—0
Few-Shot Unsupervised Image-to-Image Translation on complex scenes—0
GAIT: Gradient Adjusted Unsupervised Image-to-Image Translation—0
Image-to-image Mapping with Many Domains by Sparse Attribute Transfer—0
Image-to-Image Translation Based on Deep Generative Modeling for Radiotherapy Synthetic Dataset Creation—0
Improving Style-Content Disentanglement in Image-to-Image Translation—0
Invertible Autoencoder for domain adaptation—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