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 51–60 of 124 papers

TitleStatusHype
Combining Noise-to-Image and Image-to-Image GANs: Brain MR Image Augmentation for Tumor Detection—0
Latent Filter Scaling for Multimodal Unsupervised Image-to-Image Translation—0
Enhanced Unsupervised Image-to-Image Translation Using Contrastive Learning and Histogram of Oriented Gradients—0
Joint haze image synthesis and dehazing with mmd-vae losses—0
Mutual-GAN: Towards Unsupervised Cross-Weather Adaptation with Mutual Information Constraint—0
On the Role of Receptive Field in Unsupervised Sim-to-Real Image Translation—0
Self-Supervised Dense Consistency Regularization for Image-to-Image Translation—0
Invertible Autoencoder for domain adaptation—0
Multi-cropping Contrastive Learning and Domain Consistency for Unsupervised Image-to-Image Translation—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