SOTAVerified

Synthetic-to-Real Translation

Synthetic-to-real translation is the task of domain adaptation from synthetic (or virtual) data to real data.

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Papers

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Showing 41–50 of 68 papers

TitleStatusHype
Diverse Image-to-Image Translation via Disentangled RepresentationsCode1
Learning Content-enhanced Mask Transformer for Domain Generalized Urban-Scene SegmentationCode0
ELDA: Using Edges to Have an Edge on Semantic Segmentation Based UDACode0
G2L: A Global to Local Alignment Method for Unsupervised Domain Adaptive Semantic Segmentation—0
TridentAdapt: Learning Domain-invariance via Source-Target Confrontation and Self-induced Cross-domain AugmentationCode0
Pixel-level Intra-domain Adaptation for Semantic Segmentation—0
Domain Adaptive Semantic Segmentation via Regional Contrastive Consistency RegularizationCode0
Unsupervised Domain Adaptation for Semantic Segmentation via Low-level Edge Information Transfer—0
Cross-Region Domain Adaptation for Class-level Alignment—0
Exploiting Image Translations via Ensemble Self-Supervised Learning for Unsupervised Domain Adaptation—0
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