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

Relying on monocular image data for precise 3D object detection remains anopen problem, whose solution has broad implications for cost-sensitiveapplications such as traffic monitoring. We present UrbanNet, a modulararchitecture for long range monocular 3D object detection with static cameras.Our proposed system combines commonly available urban maps along with a mature2D object detector and an efficient 3D object descriptor to accomplish accuratedetection at long range even when objects are rotated along any of their threeaxes. We evaluate UrbanNet on a novel challenging synthetic dataset andhighlight the advantages of its design for traffic detection in roads withchanging slope, where the flat ground approximation does not hold. Data andcode are available at https://github.com/TRAILab/UrbanNet

UrbanNet: Leveraging Urban Maps for Long Range 3D Object Detection