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 21–30 of 68 papers

TitleStatusHype
PixMatch: Unsupervised Domain Adaptation via Pixelwise Consistency TrainingCode1
Self-supervised Augmentation Consistency for Adapting Semantic SegmentationCode1
Domain Adaptive Semantic Segmentation with Self-Supervised Depth EstimationCode1
Adaptive Boosting for Domain Adaptation: Towards Robust Predictions in Scene SegmentationCode1
MetaCorrection: Domain-aware Meta Loss Correction for Unsupervised Domain Adaptation in Semantic SegmentationCode1
Prototypical Pseudo Label Denoising and Target Structure Learning for Domain Adaptive Semantic SegmentationCode1
Pixel-Level Cycle Association: A New Perspective for Domain Adaptive Semantic SegmentationCode1
Permuted AdaIN: Reducing the Bias Towards Global Statistics in Image ClassificationCode1
Instance Adaptive Self-Training for Unsupervised Domain AdaptationCode1
Content-Consistent Matching for Domain Adaptive Semantic SegmentationCode1
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