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

Due to the prevalence of social media websites, one challenge facing computervision researchers is to devise methods to process and search for persons ofinterest among the billions of shared photos on these websites. Facebookrevealed in a 2013 white paper that its users have uploaded more than 250billion photos, and are uploading 350 million new photos each day. Due to thishumongous amount of data, large-scale face search for mining web images is bothimportant and challenging. Despite significant progress in face recognition,searching a large collection of unconstrained face images has not beenadequately addressed. To address this challenge, we propose a face searchsystem which combines a fast search procedure, coupled with a state-of-the-artcommercial off the shelf (COTS) matcher, in a cascaded framework. Given a probeface, we first filter the large gallery of photos to find the top-k mostsimilar faces using deep features generated from a convolutional neuralnetwork. The k candidates are re-ranked by combining similarities from deepfeatures and the COTS matcher. We evaluate the proposed face search system on agallery containing 80 million web-downloaded face images. Experimental resultsdemonstrate that the deep features are competitive with state-of-the-artmethods on unconstrained face recognition benchmarks (LFW and IJB-A). Further,the proposed face search system offers an excellent trade-off between accuracyand scalability on datasets consisting of millions of images. Additionally, inan experiment involving searching for face images of the Tsarnaev brothers,convicted of the Boston Marathon bombing, the proposed face search system couldfind the younger brother's (Dzhokhar Tsarnaev) photo at rank 1 in 1 second on a5M gallery and at rank 8 in 7 seconds on an 80M gallery.

Face Search at Scale: 80 Million Gallery