computer-vision-1
Grounded Multiple Object Tracking
3260 papers • 126 benchmarks • 313 datasets
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Most implemented papers
TP-GMOT: Tracking Generic Multiple Object by Textual Prompt with Motion-Appearance Cost (MAC) SORT
Anh Duy Le Dinh, Kim Hoang Tran, N. Le•Tue Sep 03 2024
A novel text prompt-based open-vocabulary GMOT framework, called TP-GMOT, which can track never-seen object categories with zero training examples and introduces Motion-Appearance Cost SORT, a novel object association approach that adeptly integrates motion and appearance-based matching strategies to tackle the complex task of tracking multiple generic objects with high similarity.