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 Tools annual

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 Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Stickers have become a ubiquitous part of modern-day communication, conveyingcomplex emotions through visual imagery. To facilitate the development of morepowerful algorithms for analyzing stickers, we propose a large-scale Chinesesticker dataset, namely Sticker820K, which consists of 820k image-text pairs.Each sticker has rich and high-quality textual annotations, includingdescriptions, optical characters, emotional labels, and style classifications.Although vision-language tasks in the domain of natural images have been wellstudied, directly applying the those models, such as CLIP, to sticker data isnot an optimal solution due to the discrepant nature between natural andemotive image data. Therefore, we propose StickerCLIP as a benchmark model onthe Sticker820K dataset. For the text-to-image retrieval task, our StickerCLIPdemonstrates strong superiority over the CLIP, which achieves an absolute gainof 66.0\% in mean recall on the Sticker820K test set. Additionally, we endeavorto extend the recently popularized LLM by means of prompt tuning, integratingits ability for sticker retrieval and allowing users to retrieve stickersthrough instructions. We validate the feasibility of this method, demonstratingthe immense potential of prompt tuning in expanding LLM abilities while notaffecting the quality of upstream tasks.

Sticker820K: Empowering Interactive Retrieval with Stickers