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

Volume rendering using neural fields has shown great promise in capturing andsynthesizing novel views of 3D scenes. However, this type of approach requiresquerying the volume network at multiple points along each viewing ray in orderto render an image, resulting in very slow rendering times. In this paper, wepresent a method that overcomes this limitation by learning a direct mappingfrom camera rays to locations along the ray that are most likely to influencethe pixel's final appearance. Using this approach we are able to render, trainand fine-tune a volumetrically-rendered neural field model an order ofmagnitude faster than standard approaches. Unlike existing methods, ourapproach works with general volumes and can be trained end-to-end.

TermiNeRF: Ray Termination Prediction for Efficient Neural Rendering