Office-Caltech10

Domain adaptation (DA) aims to transfer discriminative features learned from source domain to target domain. Most of DA methods focus on enhancing feature transferability through domain-invariance learning. However, source-learned discriminability itself might be tailored to be biased and unsafely transferable by spurious correlations, i.e., part of source-speciļ¬c features are correlated with category labels.

Data and Resources

Cite this as

Z. Deng, Y. Luo, J. Zhu (2024). Dataset: Office-Caltech10. https://doi.org/10.57702/gds3bkkt

DOI retrieved: December 3, 2024

Additional Info

Field Value
Created December 3, 2024
Last update December 3, 2024
Defined In https://doi.org/10.48550/arXiv.2404.06599
Citation
  • https://doi.org/10.1109/TKDE.2021.3119185
  • https://doi.org/10.48550/arXiv.2011.03737
Author Z. Deng
More Authors
Y. Luo
J. Zhu
Homepage https://cs.nyu.edu/~ylclab/research/datasets/office-31.html