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

We introduce VISUALCENT, a unified human pose and instance segmentationframework to address generalizability and scalability limitations to multiperson visual human analysis. VISUALCENT leverages centroid based bottom upkeypoint detection paradigm and uses Keypoint Heatmap incorporating DiskRepresentation and KeyCentroid to identify the optimal keypoint coordinates.For the unified segmentation task, an explicit keypoint is defined as a dynamiccentroid called MaskCentroid to swiftly cluster pixels to specific humaninstance during rapid changes in human body movement or significantly occludedenvironment. Experimental results on COCO and OCHuman datasets demonstrateVISUALCENTs accuracy and real time performance advantages, outperformingexisting methods in mAP scores and execution frame rate per second. Theimplementation is available on the project page.

VISUALCENT: Visual Human Analysis using Dynamic Centroid Representation