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 31–40 of 68 papers

TitleStatusHype
Classes Matter: A Fine-grained Adversarial Approach to Cross-domain Semantic SegmentationCode1
DACS: Domain Adaptation via Cross-domain Mixed SamplingCode1
StereoGAN: Bridging Synthetic-to-Real Domain Gap by Joint Optimization of Domain Translation and Stereo MatchingCode1
Unsupervised Intra-domain Adaptation for Semantic Segmentation through Self-SupervisionCode1
Rectifying Pseudo Label Learning via Uncertainty Estimation for Domain Adaptive Semantic SegmentationCode1
Unsupervised Scene Adaptation with Memory Regularization in vivoCode1
Confidence Regularized Self-TrainingCode1
Bidirectional Learning for Domain Adaptation of Semantic SegmentationCode1
A Curriculum Domain Adaptation Approach to the Semantic Segmentation of Urban ScenesCode1
ADVENT: Adversarial Entropy Minimization for Domain Adaptation in Semantic SegmentationCode1
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