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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 61–68 of 68 papers

Title	Date	Tasks	Status	Hype
TridentAdapt: Learning Domain-invariance via Source-Target Confrontation and Self-induced Cross-domain Augmentation	Nov 30, 2021	Data AugmentationDomain Adaptation	CodeCode Available	0
Category Anchor-Guided Unsupervised Domain Adaptation for Semantic Segmentation	Oct 29, 2019	Domain AdaptationSemantic Segmentation	CodeCode Available	0
Constructing Self-motivated Pyramid Curriculums for Cross-Domain Semantic Segmentation: A Non-Adversarial Approach	Aug 26, 2019	Domain AdaptationSegmentation	CodeCode Available	0
Learning Content-enhanced Mask Transformer for Domain Generalized Urban-Scene Segmentation	Jul 1, 2023	DecoderDomain Adaptation	CodeCode Available	0
Curriculum Domain Adaptation for Semantic Segmentation of Urban Scenes	Jul 29, 2017	Autonomous DrivingDomain Adaptation	CodeCode Available	0
CyCADA: Cycle-Consistent Adversarial Domain Adaptation	Nov 8, 2017	Domain AdaptationImage-to-Image Translation	CodeCode Available	0
Learning from Scale-Invariant Examples for Domain Adaptation in Semantic Segmentation	Jul 28, 2020	Domain AdaptationImage-to-Image Translation	CodeCode Available	0
Learning to Adapt Structured Output Space for Semantic Segmentation	Feb 28, 2018	Domain AdaptationImage-to-Image Translation	CodeCode Available	0

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