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

We present ARTrackV2, which integrates two pivotal aspects of tracking:determining where to look (localization) and how to describe (appearanceanalysis) the target object across video frames. Building on the foundation ofits predecessor, ARTrackV2 extends the concept by introducing a unifiedgenerative framework to "read out" object's trajectory and "retell" itsappearance in an autoregressive manner. This approach fosters a time-continuousmethodology that models the joint evolution of motion and visual features,guided by previous estimates. Furthermore, ARTrackV2 stands out for itsefficiency and simplicity, obviating the less efficient intra-frameautoregression and hand-tuned parameters for appearance updates. Despite itssimplicity, ARTrackV2 achieves state-of-the-art performance on prevailingbenchmark datasets while demonstrating remarkable efficiency improvement. Inparticular, ARTrackV2 achieves AO score of 79.5\% on GOT-10k, and AUC of 86.1\%on TrackingNet while being $3.6 \times$ faster than ARTrack. The code will bereleased.

ARTrackV2: Prompting Autoregressive Tracker Where to Look and How to Describe