Browse > Methodology > Domain Adaptation > Unsupervised Domain Adaptation

Unsupervised Domain Adaptation

47 papers with code · Methodology
Subtask of Domain Adaptation

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Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks

CVPR 2017 tensorflow/models

Collecting well-annotated image datasets to train modern machine learning algorithms is prohibitively expensive for many tasks.

UNSUPERVISED DOMAIN ADAPTATION

Domain Separation Networks

NeurIPS 2016 tensorflow/models

However, by focusing only on creating a mapping or shared representation between the two domains, they ignore the individual characteristics of each domain.

UNSUPERVISED DOMAIN ADAPTATION

Visual Domain Adaptation with Manifold Embedded Distribution Alignment

19 Jul 2018jindongwang/transferlearning

Existing methods either attempt to align the cross-domain distributions, or perform manifold subspace learning.

UNSUPERVISED DOMAIN ADAPTATION

A Survey of Unsupervised Deep Domain Adaptation

6 Dec 2018zhaoxin94/awsome-domain-adaptation

Deep learning has produced state-of-the-art results for a variety of tasks.

TRANSFER LEARNING UNSUPERVISED DOMAIN ADAPTATION

Correlation Alignment for Unsupervised Domain Adaptation

6 Dec 2016eridgd/WCT-TF

In contrast to subspace manifold methods, it aligns the original feature distributions of the source and target domains, rather than the bases of lower-dimensional subspaces.

UNSUPERVISED DOMAIN ADAPTATION

Maximum Classifier Discrepancy for Unsupervised Domain Adaptation

CVPR 2018 mil-tokyo/MCD_DA

To solve these problems, we introduce a new approach that attempts to align distributions of source and target by utilizing the task-specific decision boundaries.

IMAGE CLASSIFICATION SEMANTIC SEGMENTATION UNSUPERVISED DOMAIN ADAPTATION

Adversarial Discriminative Domain Adaptation

CVPR 2017 erictzeng/adda

Adversarial learning methods are a promising approach to training robust deep networks, and can generate complex samples across diverse domains.

OBJECT CLASSIFICATION UNSUPERVISED DOMAIN ADAPTATION UNSUPERVISED IMAGE-TO-IMAGE TRANSLATION

A DIRT-T Approach to Unsupervised Domain Adaptation

ICLR 2018 domainadaptation/salad

Domain adaptation refers to the problem of leveraging labeled data in a source domain to learn an accurate model in a target domain where labels are scarce or unavailable.

UNSUPERVISED DOMAIN ADAPTATION

Deep CORAL: Correlation Alignment for Deep Domain Adaptation

6 Jul 2016domainadaptation/salad

CORAL is a "frustratingly easy" unsupervised domain adaptation method that aligns the second-order statistics of the source and target distributions with a linear transformation.

UNSUPERVISED DOMAIN ADAPTATION

Learning to cluster in order to transfer across domains and tasks

ICLR 2018 GT-RIPL/L2C

The key insight is that, in addition to features, we can transfer similarity information and this is sufficient to learn a similarity function and clustering network to perform both domain adaptation and cross-task transfer learning.

TRANSFER LEARNING UNSUPERVISED DOMAIN ADAPTATION