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

In recent years, both online retail and video hosting service areexponentially growing. In this paper, we explore a new cross-domain task,Video2Shop, targeting for matching clothes appeared in videos to the exact sameitems in online shops. A novel deep neural network, called AsymNet, is proposedto explore this problem. For the image side, well-established methods are usedto detect and extract features for clothing patches with arbitrary sizes. Forthe video side, deep visual features are extracted from detected object regionsin each frame, and further fed into a Long Short-Term Memory (LSTM) frameworkfor sequence modeling, which captures the temporal dynamics in videos. Toconduct exact matching between videos and online shopping images, LSTM hiddenstates, representing the video, and image features, which represent staticobject images, are jointly modeled under the similarity network withreconfigurable deep tree structure. Moreover, an approximate training method isproposed to achieve the efficiency when training. Extensive experimentsconducted on a large cross-domain dataset have demonstrated the effectivenessand efficiency of the proposed AsymNet, which outperforms the state-of-the-artmethods.

Video2Shop: Exact Matching Clothes in Videos to Online Shopping Images