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About this paper
Mohamad Alansari, Muzammal Naseer, Hasan Al Marzouqi, Naoufel Werghi, Sajid Javed
Researchers from Khalifa University introduce a unified hybrid memory framework for SAM-based visual object tracking, addressing fragmented memory designs and uncertain transferability to next-generation foundation models. The framework decomposes memory into short-term appearance and long-term distractor resolution components, demonstrating improved tracking robustness by integrating existing memory policies with SAM2 and SAM3 backbones.
Key insights
- Sophisticated memory design remains a critical bottleneck for SAM-based tracking, even when utilizing stronger foundation models like SAM3, which benefit from explicit memory mechanisms beyond default confidence-based retention.
- The decomposition of memory into complementary short-term and long-term components provides a modular and principled way to combine existing memory policies, exploiting their individual strengths.
- Memory-aware designs are crucial for long-term stability in SAM-based tracking, as naive FIFO memory updates inherently lead to error accumulation.
Summary by alphaXiv.
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