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A Testbed for Cross-Dataset Analysis

  • Tatiana TommasiEmail author
  • Tinne Tuytelaars
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8927)

Abstract

Despite the increasing interest towards domain adaptation and transfer learning techniques to generalize over image collections and overcome their biases, the visual community misses a large scale testbed for cross-dataset analysis. In this paper we discuss the challenges faced when aligning twelve existing image databases in a unique corpus, and we propose two cross-dataset setups that introduce new interesting research questions. Moreover, we report on a first set of experimental domain adaptation tests showing the effectiveness of iterative self-labeling for large scale problems.

Keywords

Dataset Bias Domain Adaptation Iterative Self-Labeling 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.ESAT-PSI/VISICS - iMindsKU LeuvenBelgium

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