Who Cited It

Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks

2017 · 1,634 citations · 3 from inside this corpus

Konstantinos Bousmalis low, Nathan Silberman, David Dohan low, Dumitru Erhan, Dilip Krishnan

The source holds an abstract for this work, but its best open-access copy is under no open licence, which does not permit us to republish the text. Read it at the source below.

Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks (2017)Unsupervised Pixel-Level Doma…Adam: A Method for Stochastic Optimization (2014)Adam: A Method for Stochastic…[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics… (2015)[No title in the source recor…Domain-Adversarial Training of Neural Networks (2017)Domain-Adversarial Training o…Adapting Visual Category Models to New Domains (2010)Adapting Visual Category Mode…Learning Transferable Features with Deep Adaptation Networks (2015)Learning Transferable Feature…Unsupervised Domain Adaptation by Backpropagation (2014)Unsupervised Domain Adaptatio…Deep Domain Confusion: Maximizing for Domain Invariance (2014)Deep Domain Confusion: Maximi…A kernel two-sample test (2012)A kernel two-sample testGeodesic flow kernel for unsupervised domain adaptation (2012)Geodesic flow kernel for unsu…Return of Frustratingly Easy Domain Adaptation (2016)Return of Frustratingly Easy …Target-driven visual navigation in indoor scenes using deep reinforcement learning (2017)Target-driven visual navigati…Maximum Classifier Discrepancy for Unsupervised Domain Adaptation (2018)Maximum Classifier Discrepanc…Deep visual domain adaptation: A survey (2018)Deep visual domain adaptation…A State-of-the-Art Survey on Deep Learning Theory and Architectures (2019)A State-of-the-Art Survey on …
14 of 14 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.
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What this paper cites, inside the corpus

PaperYearCited
Adam: A Method for Stochastic Optimization201484,698
[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…201550,396
Domain-Adversarial Training of Neural Networks20177,702
Adapting Visual Category Models to New Domains20102,873
Learning Transferable Features with Deep Adaptation Networks20152,839
Unsupervised Domain Adaptation by Backpropagation20142,608
Deep Domain Confusion: Maximizing for Domain Invariance20142,354
A kernel two-sample test20122,224
Geodesic flow kernel for unsupervised domain adaptation20122,219
Return of Frustratingly Easy Domain Adaptation20161,910
Target-driven visual navigation in indoor scenes using deep reinforcement learning20171,520

What cites it, inside the corpus

PaperYearCited
Maximum Classifier Discrepancy for Unsupervised Domain Adaptation20182,280
Deep visual domain adaptation: A survey20182,232
A State-of-the-Art Survey on Deep Learning Theory and Architectures20191,619

Links

DOI · OpenAlex record

Topics

Domain Adaptation and Few-Shot LearningComputer Science
Generative Adversarial Networks and Image SynthesisComputer Science
Multimodal Machine Learning ApplicationsComputer Science

Is this record sound?

complete

Nothing in this record contradicts itself and no field we check is missing.

  • supports5 author record(s) attached.
  • supports70 reference(s) recorded.
  • supportsThe DOI's year agrees with the publication year.
  • supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:56+00:00.

sha256 7bc26169e93749d1…