AutoDIAL: Automatic Domain Alignment Layers

  title={AutoDIAL: Automatic Domain Alignment Layers},
  author={Fabio Maria Carlucci and Lorenzo Porzi and Barbara Caputo and Elisa Ricci and Samuel Rota Bul{\`o}},
  journal={2017 IEEE International Conference on Computer Vision (ICCV)},
Classifiers trained on given databases perform poorly when tested on data acquired in different settings. This is explained in domain adaptation through a shift among distributions of the source and target domains. Attempts to align them have traditionally resulted in works reducing the domain shift by introducing appropriate loss terms, measuring the discrepancies between source and target distributions, in the objective function. Here we take a different route, proposing to align the learned… CONTINUE READING
Highly Cited
This paper has 59 citations. REVIEW CITATIONS
Recent Discussions
This paper has been referenced on Twitter 22 times over the past 90 days. VIEW TWEETS


Publications citing this paper.
Showing 1-10 of 35 extracted citations

60 Citations

Citations per Year
Semantic Scholar estimates that this publication has 60 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.
Showing 1-10 of 35 references

Similar Papers

Loading similar papers…