Jointly optimising relevance and diversity in image retrieval

In this paper we present a method to jointly optimise the relevance and the diversity of the results in image retrieval. Without considering diversity, image retrieval systems often mainly find a set of very similar results, so called near duplicates, which is often not the desired behaviour. From the user perspective, the ideal result consists of documents… CONTINUE READING

9 Figures & Tables



Citations per Year

99 Citations

Semantic Scholar estimates that this publication has 99 citations based on the available data.

See our FAQ for additional information.

  • Blog articles referencing this paper

  • Presentations referencing similar topics