The paper defines the 4DVLT task for worldline-centered 4D scene understanding, releases Instruct-4D with 129.4K QA pairs, and presents 4DTrack achieving 62.68 TGA_Top1, outperforming adapted baselines by 19.62 points.
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TrackingNet: A large-scale dataset and benchmark for object tracking in the wild
2 Pith papers cite this work, alongside 1,100 external citations. Polarity classification is still indexing.
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Hybrid ANN-CANN network for visual object tracking that operationalizes bias-variance complementarity to outperform baselines on nine benchmarks.
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4DVLT: Dynamic Scene Understanding with Worldline-Centered Vision-Language Tracking
The paper defines the 4DVLT task for worldline-centered 4D scene understanding, releases Instruct-4D with 129.4K QA pairs, and presents 4DTrack achieving 62.68 TGA_Top1, outperforming adapted baselines by 19.62 points.