SOTAVerified

Synthetic-to-Real Translation

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

( Image credit: CYCADA )

Papers

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Showing 41–50 of 68 papers

TitleStatusHype
Instance Adaptive Self-Training for Unsupervised Domain AdaptationCode1
Content-Consistent Matching for Domain Adaptive Semantic SegmentationCode1
Learning from Scale-Invariant Examples for Domain Adaptation in Semantic SegmentationCode0
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
Deep CG2Real: Synthetic-to-Real Translation via Image Disentanglement—0
Rectifying Pseudo Label Learning via Uncertainty Estimation for Domain Adaptive Semantic SegmentationCode1
Unsupervised Scene Adaptation with Memory Regularization in vivoCode1
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