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 11–20 of 124 papers

TitleStatusHype
Multi-cropping Contrastive Learning and Domain Consistency for Unsupervised Image-to-Image Translation—0
Domain-knowledge Inspired Pseudo Supervision (DIPS) for Unsupervised Image-to-Image Translation Models to Support Cross-Domain ClassificationCode0
Standardized CycleGAN training for unsupervised stain adaptation in invasive carcinoma classification for breast histopathology—0
Self-FuseNet: Data Free Unsupervised Remote Sensing Image Super-Resolution—0
Augmenting Ego-Vehicle for Traffic Near-Miss and Accident Classification Dataset using Manipulating Conditional Style TranslationCode0
DGFont++: Robust Deformable Generative Networks for Unsupervised Font GenerationCode2
A Framework for Generalizing Critical Heat Flux Detection Models Using Unsupervised Image-to-Image Translation—0
LANIT: Language-Driven Image-to-Image Translation for Unlabeled DataCode1
Learning to Incorporate Texture Saliency Adaptive Attention to Image CartoonizationCode1
Unsupervised Image-to-Image Translation with Generative PriorCode1
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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