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 1–25 of 124 papers

TitleStatusHype
Multi-Platform Methane Plume Detection via Model and Domain Adaptation—0
Adversarial Wear and Tear: Exploiting Natural Damage for Generating Physical-World Adversarial Examples—0
Semantically Robust Unsupervised Image Translation for Paired Remote Sensing Images—0
Unpaired Image-to-Image Translation with Content Preserving Perspective: A Review—0
Enhanced Unsupervised Image-to-Image Translation Using Contrastive Learning and Histogram of Oriented Gradients—0
Image-to-Image Translation Based on Deep Generative Modeling for Radiotherapy Synthetic Dataset Creation—0
Dense Multitask Learning to Reconfigure Comics—0
GP-UNIT: Generative Prior for Versatile Unsupervised Image-to-Image TranslationCode1
Variational Bayesian Framework for Advanced Image Generation with Domain-Related Variables—0
Wavelet-based Unsupervised Label-to-Image TranslationCode0
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
A Style-aware Discriminator for Controllable Image TranslationCode1
Learning to generate line drawings that convey geometry and semanticsCode2
Deep Learning-Assisted Co-registration of Full-Spectral Autofluorescence Lifetime Microscopic Images with H&E-Stained Histology ImagesCode1
Multi-domain Unsupervised Image-to-Image Translation with Appearance Adaptive Convolution—0
Self-Supervised Dense Consistency Regularization for Image-to-Image Translation—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