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Domain Generalization

16 papers with code · Methodology
Subtask of Domain Adaptation

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Greatest papers with code

A Closer Look at Few-shot Classification

ICLR 2019 wyharveychen/CloserLookFewShot

Few-shot classification aims to learn a classifier to recognize unseen classes during training with limited labeled examples.

DOMAIN GENERALIZATION FEW-SHOT IMAGE CLASSIFICATION FEW-SHOT LEARNING

A Closer Look at Few-shot Classification

ICLR 2019 wyharveychen/CloserLookFewShot

Few-shot classification aims to learn a classifier to recognize unseen classes during training with limited labeled examples.

DOMAIN GENERALIZATION FEW-SHOT IMAGE CLASSIFICATION FEW-SHOT LEARNING

A Generalization Error Bound for Multi-class Domain Generalization

24 May 2019amber0309/Domain-generalization

Domain generalization is the problem of assigning labels to an unlabeled data set, given several similar data sets for which labels have been provided.

DOMAIN GENERALIZATION

Domain Generalization by Solving Jigsaw Puzzles

16 Mar 2019amber0309/Domain-generalization

Human adaptability relies crucially on the ability to learn and merge knowledge both from supervised and unsupervised learning: the parents point out few important concepts, but then the children fill in the gaps on their own.

DOMAIN GENERALIZATION OBJECT RECOGNITION

Episodic Training for Domain Generalization

31 Jan 2019amber0309/Domain-generalization

Domain generalization (DG) is the challenging and topical problem of learning models that generalize to novel testing domain with different statistics than a set of known training domains.

DOMAIN GENERALIZATION

Domain Generalization by Marginal Transfer Learning

21 Nov 2017amber0309/Domain-generalization

Domain generalization is the problem of assigning class labels to an unlabeled test data set, given several labeled training data sets drawn from similar distributions.

DOMAIN GENERALIZATION TRANSFER LEARNING

Domain Generalization by Solving Jigsaw Puzzles

CVPR 2019 fmcarlucci/JigenDG

Human adaptability relies crucially on the ability to learn and merge knowledge both from supervised and unsupervised learning: the parents point out few important concepts, but then the children fill in the gaps on their own.

DOMAIN GENERALIZATION OBJECT RECOGNITION

Domain Generalization for Object Recognition with Multi-task Autoencoders

ICCV 2015 ghif/mtae

The problem of domain generalization is to take knowledge acquired from a number of related domains where training data is available, and to then successfully apply it to previously unseen domains.

DENOISING DOMAIN GENERALIZATION OBJECT RECOGNITION