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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Solid texture synthesis (STS), an effective way to extend a 2D exemplar to a3D solid volume, exhibits advantages in computational photography. However,existing methods generally fail to accurately learn arbitrary textures, whichmay result in the failure to synthesize solid textures with high fidelity. Inthis paper, we propose a novel generative adversarial nets-based framework(STS-GAN) to extend the given 2D exemplar to arbitrary 3D solid textures. InSTS-GAN, multi-scale 2D texture discriminators evaluate the similarity betweenthe given 2D exemplar and slices from the generated 3D texture, promoting the3D texture generator synthesizing realistic solid textures. Finally,experiments demonstrate that the proposed method can generate high-fidelitysolid textures with similar visual characteristics to the 2D exemplar.

STS-GAN: Can We Synthesize Solid Texture with High Fidelity from Arbitrary 2D Exemplar?