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

Recent works have shown that 3D-aware GANs trained on unstructured singleimage collections can generate multiview images of novel instances. The keyunderpinnings to achieve this are a 3D radiance field generator and a volumerendering process. However, existing methods either cannot generatehigh-resolution images (e.g., up to 256X256) due to the high computation costof neural volume rendering, or rely on 2D CNNs for image-space upsampling whichjeopardizes the 3D consistency across different views. This paper proposes anovel 3D-aware GAN that can generate high resolution images (up to 1024X1024)while keeping strict 3D consistency as in volume rendering. Our motivation isto achieve super-resolution directly in the 3D space to preserve 3Dconsistency. We avoid the otherwise prohibitively-expensive computation cost byapplying 2D convolutions on a set of 2D radiance manifolds defined in therecent generative radiance manifold (GRAM) approach, and apply dedicated lossfunctions for effective GAN training at high resolution. Experiments on FFHQand AFHQv2 datasets show that our method can produce high-quality 3D-consistentresults that significantly outperform existing methods. It makes a significantstep towards closing the gap between traditional 2D image generation and3D-consistent free-view generation.

GRAM-HD: 3D-Consistent Image Generation at High Resolution with Generative Radiance Manifolds