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

NeRF acquisition typically requires careful choice of near planes for thedifferent cameras or suffers from background collapse, creating floatingartifacts on the edges of the captured scene. The key insight of this work isthat background collapse is caused by a higher density of samples in regionsnear cameras. As a result of this sampling imbalance, near-camera volumesreceive significantly more gradients, leading to incorrect density buildup. Wepropose a gradient scaling approach to counter-balance this sampling imbalance,removing the need for near planes, while preventing background collapse. Ourmethod can be implemented in a few lines, does not induce any significantoverhead, and is compatible with most NeRF implementations.

Floaters No More: Radiance Field Gradient Scaling for Improved Near-Camera Training