AI RESEARCH
Event-Adaptive State Transition and Gated Fusion for RGB-Event Object Tracking
arXiv CS.AI
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ArXi:2604.13426v1 Announce Type: cross Existing Vision Mamba-based RGB-Event(RGBE) tracking methods suffer from using static state transition matrices, which fail to adapt to variations in event sparsity. This rigidity leads to imbalanced modeling-underfitting sparse event streams and overfitting dense ones-thus degrading cross-modal fusion robustness. To address these limitations, we propose MambaTrack, a multimodal and efficient tracking framework built upon a Dynamic State Space Model(DSSM). Our contributions are twofold. First, we.