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

Photo-to-caricature translation aims to synthesize the caricature as arendered image exaggerating the features through sketching, pencil strokes, orother artistic drawings. Style rendering and geometry deformation are the mostimportant aspects in photo-to-caricature translation task. To take both intoconsideration, we propose an unsupervised contrastive photo-to-caricaturetranslation architecture. Considering the intuitive artifacts in the existingmethods, we propose a contrastive style loss for style rendering to enforce thesimilarity between the style of rendered photo and the caricature, andsimultaneously enhance its discrepancy to the photos. To obtain an exaggeratingdeformation in an unpaired/unsupervised fashion, we propose a DistortionPrediction Module (DPM) to predict a set of displacements vectors for eachinput image while fixing some controlling points, followed by the thin platespline interpolation for warping. The model is trained on unpaired photo andcaricature while can offer bidirectional synthesizing via inputting either aphoto or a caricature. Extensive experiments demonstrate that the proposedmodel is effective to generate hand-drawn like caricatures compared withexisting competitors.

Unsupervised Contrastive Photo-to-Caricature Translation based on Auto-distortion