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 71–80 of 124 papers

TitleStatusHype
Learning Unsupervised Cross-domain Image-to-Image Translation Using a Shared DiscriminatorCode0
Six-channel Image Representation for Cross-domain Object Detection—0
Minimal Geometry-Distortion Constraint for Unsupervised Image-to-Image Translation—0
Learning Energy-Based Generative Models via Coarse-to-Fine Expanding and Sampling—0
GAIT: Gradient Adjusted Unsupervised Image-to-Image Translation—0
Crossing-Domain Generative Adversarial Networks for Unsupervised Multi-Domain Image-to-Image Translation—0
Improving Style-Content Disentanglement in Image-to-Image Translation—0
MCMI: Multi-Cycle Image Translation with Mutual Information ConstraintsCode0
Image-to-image Mapping with Many Domains by Sparse Attribute Transfer—0
Medical Image Generation using Generative Adversarial Networks—0
Show:102550
← PrevPage 8 of 13Next →
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