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 this paper, we present a large-scale detailed 3D face dataset, FaceScape,and propose a novel algorithm that is able to predict elaborate riggable 3Dface models from a single image input. FaceScape dataset provides 18,760textured 3D faces, captured from 938 subjects and each with 20 specificexpressions. The 3D models contain the pore-level facial geometry that is alsoprocessed to be topologically uniformed. These fine 3D facial models can berepresented as a 3D morphable model for rough shapes and displacement maps fordetailed geometry. Taking advantage of the large-scale and high-accuracydataset, a novel algorithm is further proposed to learn the expression-specificdynamic details using a deep neural network. The learned relationship serves asthe foundation of our 3D face prediction system from a single image input.Different than the previous methods, our predicted 3D models are riggable withhighly detailed geometry under different expressions. The unprecedented datasetand code will be released to public for research purpose.

FaceScape: a Large-scale High Quality 3D Face Dataset and Detailed Riggable 3D Face Prediction