Unsupervised Visual Domain Adaptation Using Subspace Alignment
Basura Fernando, Amaury Habrard, Marc Sebban, Tinne Tuytelaars
The source holds an abstract for this work, but its best open-access copy is under other-oa, which does not permit us to republish the text. Read it at the source below.
this paper
works it cites
works citing it
node size = global citations · hover for the full title
Citation edge evidence
- Domain-Adversarial Training of Neural Networks→Unsupervised Visual Domain Adaptation Using Subspace AlignmentLegacy edge — source detail unavailable
- A Comprehensive Survey on Transfer Learning→Unsupervised Visual Domain Adaptation Using Subspace AlignmentLegacy edge — source detail unavailable
- Deep CORAL: Correlation Alignment for Deep Domain Adaptation→Unsupervised Visual Domain Adaptation Using Subspace AlignmentLegacy edge — source detail unavailable
- Unsupervised Domain Adaptation by Backpropagation→Unsupervised Visual Domain Adaptation Using Subspace AlignmentLegacy edge — source detail unavailable
- Deep Domain Confusion: Maximizing for Domain Invariance→Unsupervised Visual Domain Adaptation Using Subspace AlignmentLegacy edge — source detail unavailable
- Deep Hashing Network for Unsupervised Domain Adaptation→Unsupervised Visual Domain Adaptation Using Subspace AlignmentLegacy edge — source detail unavailable
- Return of Frustratingly Easy Domain Adaptation→Unsupervised Visual Domain Adaptation Using Subspace AlignmentLegacy edge — source detail unavailable
- Unsupervised Visual Domain Adaptation Using Subspace Alignment→Adapting Visual Category Models to New DomainsLegacy edge — source detail unavailable
- Unsupervised Visual Domain Adaptation Using Subspace Alignment→Geodesic flow kernel for unsupervised domain adaptationLegacy edge — source detail unavailable
- Unsupervised Visual Domain Adaptation Using Subspace Alignment→Analysis of Representations for Domain AdaptationLegacy edge — source detail unavailable
- Unsupervised Visual Domain Adaptation Using Subspace Alignment→Domain adaptation with structural correspondence learningLegacy edge — source detail unavailable
- Deep Domain Confusion: Maximizing for Domain Invariance→Adapting Visual Category Models to New DomainsLegacy edge — source detail unavailable
- Deep Domain Confusion: Maximizing for Domain Invariance→Analysis of Representations for Domain AdaptationLegacy edge — source detail unavailable
- Domain-Adversarial Training of Neural Networks→Deep Domain Confusion: Maximizing for Domain InvarianceLegacy edge — source detail unavailable
- Domain-Adversarial Training of Neural Networks→Adapting Visual Category Models to New DomainsLegacy edge — source detail unavailable
- Domain-Adversarial Training of Neural Networks→Analysis of Representations for Domain AdaptationLegacy edge — source detail unavailable
- Domain-Adversarial Training of Neural Networks→Geodesic flow kernel for unsupervised domain adaptationLegacy edge — source detail unavailable
- Domain-Adversarial Training of Neural Networks→Domain adaptation with structural correspondence learningLegacy edge — source detail unavailable
- Unsupervised Domain Adaptation by Backpropagation→Deep Domain Confusion: Maximizing for Domain InvarianceLegacy edge — source detail unavailable
- Unsupervised Domain Adaptation by Backpropagation→Adapting Visual Category Models to New DomainsLegacy edge — source detail unavailable
- Analysis of Representations for Domain Adaptation→Domain adaptation with structural correspondence learningLegacy edge — source detail unavailable
- Geodesic flow kernel for unsupervised domain adaptation→Adapting Visual Category Models to New DomainsLegacy edge — source detail unavailable
- Geodesic flow kernel for unsupervised domain adaptation→Analysis of Representations for Domain AdaptationLegacy edge — source detail unavailable
- Geodesic flow kernel for unsupervised domain adaptation→Domain adaptation with structural correspondence learningLegacy edge — source detail unavailable
- Deep Hashing Network for Unsupervised Domain Adaptation→Adapting Visual Category Models to New DomainsLegacy edge — source detail unavailable
- Deep Hashing Network for Unsupervised Domain Adaptation→Domain-Adversarial Training of Neural NetworksLegacy edge — source detail unavailable
- Deep Hashing Network for Unsupervised Domain Adaptation→Geodesic flow kernel for unsupervised domain adaptationLegacy edge — source detail unavailable
- Deep Hashing Network for Unsupervised Domain Adaptation→Return of Frustratingly Easy Domain AdaptationLegacy edge — source detail unavailable
- Return of Frustratingly Easy Domain Adaptation→Deep Domain Confusion: Maximizing for Domain InvarianceLegacy edge — source detail unavailable
- Return of Frustratingly Easy Domain Adaptation→Adapting Visual Category Models to New DomainsLegacy edge — source detail unavailable
- Return of Frustratingly Easy Domain Adaptation→Unsupervised Domain Adaptation by BackpropagationLegacy edge — source detail unavailable
- Return of Frustratingly Easy Domain Adaptation→Analysis of Representations for Domain AdaptationLegacy edge — source detail unavailable
- Return of Frustratingly Easy Domain Adaptation→Geodesic flow kernel for unsupervised domain adaptationLegacy edge — source detail unavailable
- Return of Frustratingly Easy Domain Adaptation→Domain adaptation with structural correspondence learningLegacy edge — source detail unavailable
- Deep CORAL: Correlation Alignment for Deep Domain Adaptation→Deep Domain Confusion: Maximizing for Domain InvarianceLegacy edge — source detail unavailable
- Deep CORAL: Correlation Alignment for Deep Domain Adaptation→Adapting Visual Category Models to New DomainsLegacy edge — source detail unavailable
- Deep CORAL: Correlation Alignment for Deep Domain Adaptation→Geodesic flow kernel for unsupervised domain adaptationLegacy edge — source detail unavailable
- Deep CORAL: Correlation Alignment for Deep Domain Adaptation→Return of Frustratingly Easy Domain AdaptationLegacy edge — source detail unavailable
- A Comprehensive Survey on Transfer Learning→Deep Domain Confusion: Maximizing for Domain InvarianceLegacy edge — source detail unavailable
- A Comprehensive Survey on Transfer Learning→Adapting Visual Category Models to New DomainsLegacy edge — source detail unavailable
- A Comprehensive Survey on Transfer Learning→Domain-Adversarial Training of Neural NetworksLegacy edge — source detail unavailable
- A Comprehensive Survey on Transfer Learning→Unsupervised Domain Adaptation by BackpropagationLegacy edge — source detail unavailable
- A Comprehensive Survey on Transfer Learning→Geodesic flow kernel for unsupervised domain adaptationLegacy edge — source detail unavailable
- A Comprehensive Survey on Transfer Learning→Domain adaptation with structural correspondence learningLegacy edge — source detail unavailable
- A Comprehensive Survey on Transfer Learning→Return of Frustratingly Easy Domain AdaptationLegacy edge — source detail unavailable
- A Comprehensive Survey on Transfer Learning→Deep CORAL: Correlation Alignment for Deep Domain AdaptationLegacy edge — source detail unavailable
What this paper cites, inside the corpus
What cites it, inside the corpus
Links
Download BibTeX · Download RIS · DOI · Open access copy · OpenAlex record
Topics
| Domain Adaptation and Few-Shot Learning | Computer Science |
| Multimodal Machine Learning Applications | Computer Science |
| Cancer-related molecular mechanisms research | Biochemistry, Genetics and Molecular Biology |
Is this record sound?
complete
Nothing in this record contradicts itself and no field we check is missing.
- supports4 author record(s) attached.
- supports30 reference(s) recorded.
- supportsThe DOI's year agrees with the publication year.
- supportsA title is present.
Provenance
sha256 59007f057c7dae86…