English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

We exploit field guides to learn bird species recognition, in particularzero-shot recognition of unseen species. Illustrations contained in fieldguides deliberately focus on discriminative properties of each species, and canserve as side information to transfer knowledge from seen to unseen birdspecies. We study two approaches: (1) a contrastive encoding of illustrations,which can be fed into standard zero-shot learning schemes; and (2) a novelmethod that leverages the fact that illustrations are also images and as suchstructurally more similar to photographs than other kinds of side information.Our results show that illustrations from field guides, which are readilyavailable for a wide range of species, are indeed a competitive source of sideinformation for zero-shot learning. On a subset of the iNaturalist2021 datasetwith 749 seen and 739 unseen species, we obtain a classification accuracy ofunseen bird species of $12\%$ @top-1 and $38\%$ @top-10, which shows thepotential of field guides for challenging real-world scenarios with manyspecies. Our code is available at https://github.com/ac-rodriguez/zsl_billow

Recognition of Unseen Bird Species by Learning from Field Guides