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Domain Generalization

29 papers with code · Methodology
Subtask of Domain Adaptation

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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

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 by Solving Jigsaw Puzzles

16 Mar 2019fmcarlucci/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

Unified Deep Supervised Domain Adaptation and Generalization

ICCV 2017 samotiian/CCSA

This work provides a unified framework for addressing the problem of visual supervised domain adaptation and generalization with deep models.

DOMAIN GENERALIZATION

Regularized Fine-grained Meta Face Anti-spoofing

25 Nov 2019rshaojimmy/AAAI2020-RFMetaFAS

Besides, to further enhance the generalization ability of our model, the proposed framework adopts a fine-grained learning strategy that simultaneously conducts meta-learning in a variety of domain shift scenarios in each iteration.

DOMAIN GENERALIZATION FACE ANTI-SPOOFING FACE RECOGNITION META-LEARNING

A review of domain adaptation without target labels

16 Jan 2019wmkouw/libTLDA

Feature-based methods revolve around on mapping, projecting and representing features such that a source classifier performs well on the target domain and inference-based methods incorporate adaptation into the parameter estimation procedure, for instance through constraints on the optimization procedure.

DOMAIN GENERALIZATION UNSUPERVISED DOMAIN ADAPTATION

Cross-Domain Few-Shot Classification via Learned Feature-Wise Transformation

23 Jan 2020hytseng0509/CrossDomainFewShot

Few-shot classification aims to recognize novel categories with only few labeled images in each class.

DOMAIN GENERALIZATION