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Siamese-DETR for Generic Multi-Object Tracking.

Qiankun Liu, Yichen Li, Yuqi Jiang

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    Summary
    This summary is machine-generated.

    This study introduces Siamese-DETR, a novel method for Generic Multi-Object Tracking (GMOT) that effectively tracks objects using template images without needing extensive pre-training or fine-grained annotations, outperforming existing methods.

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    Area of Science:

    • Computer Vision
    • Artificial Intelligence
    • Robotics

    Background:

    • Traditional Multi-Object Tracking (MOT) is constrained to pre-defined object categories.
    • Generic MOT (GMOT) extends tracking to arbitrary objects, with Template-Image-based MOT (TIMOT) being a key approach.
    • Open-Vocabulary MOT (OVMOT) requires costly pre-trained models and detailed annotations, limiting its practical use.

    Purpose of the Study:

    • To propose Siamese-DETR, a simple yet effective method for Template-Image-based MOT (TIMOT).
    • To enable tracking of objects beyond pre-defined categories using only template images and common detection datasets.
    • To overcome the limitations of OVMOT regarding computational cost and data requirements.

    Main Methods:

    • Leveraging DETR variants' inherent object queries for tracking.
    • Designing multi-scale object queries based on template images for scale invariance.
    • Implementing a dynamic matching training strategy using standard detection datasets.
    • Simplifying the tracking pipeline via a tracking-by-query approach, replacing complex data association with Non-Maximum Suppression (NMS).

    Main Results:

    • Siamese-DETR effectively detects objects across different scales using template image information.
    • The dynamic matching strategy optimizes training on readily available detection datasets.
    • The simplified tracking pipeline achieves efficient and accurate object tracking.
    • Experimental results demonstrate superior performance of Siamese-DETR over existing MOT methods on the GMOT-40 dataset.

    Conclusions:

    • Siamese-DETR offers a practical and efficient solution for Generic Multi-Object Tracking, specifically TIMOT.
    • The method reduces reliance on expensive pre-trained models and fine-grained annotations.
    • Siamese-DETR shows significant potential for real-world applications like autonomous driving and robot navigation.