AI RESEARCH
Sparse-Dense Mixture of Experts Adapter for Multi-Modal Tracking
arXiv CS.CV
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ArXi:2603.13719v1 Announce Type: new Parameter-efficient fine-tuning (PEFT) techniques, such as prompts and adapters, are widely used in multi-modal tracking because they alleviate issues of full-model fine-tuning, including time inefficiency, high resource consumption, parameter storage burden, and catastrophic forgetting. However, due to cross-modal heterogeneity, most existing PEFT-based methods struggle to effectively represent multi-modal features within a unified framework with shared parameters.