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SotA/Methodology/Domain Adaptation/Office-Caltech

Domain Adaptation on Office-Caltech

Metric: Average Accuracy (higher is better)

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#Model↕Average Accuracy▼AugmentationsPaperDate↕Code
1SPL93NoUnsupervised Domain Adaptation via Structured Pr...2019-11-18Code
2MEDA[[Wang et al.2018]]92.8NoVisual Domain Adaptation with Manifold Embedded ...2018-07-19Code
3CAPLS [[Wang, Bu, and Breckon2019]]91.8NoUnifying Unsupervised Domain Adaptation and Zero...2019-03-25Code
4DAN[[Long et al.2015]]90.1NoLearning Transferable Features with Deep Adaptat...2015-02-10Code
5JGSA[[Zhang, Li, and Ogunbona2017]]90NoJoint Geometrical and Statistical Alignment for ...2017-05-16-
6DDC[[Tzeng et al.2014]]88.2NoDeep Domain Confusion: Maximizing for Domain Inv...2014-12-10Code
7SCA[[Ghifary et al.2016]]85.9NoScatter Component Analysis: A Unified Framework ...2015-10-15-
8CORAL[[Sun, Feng, and Saenko2017]]84.7NoCorrelation Alignment for Unsupervised Domain Ad...2016-12-06Code