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arXiv · 2506.19154

Lightweight RGB-T Tracking with Mobile Vision Transformers

Mahdi Falaki·Maria A. Amer
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Abstract

Single-modality tracking (RGB-only) struggles under low illumination, weather, and occlusion. Multimodal tracking addresses this by combining complementary cues. While Vision Transformer-based trackers achieve strong accuracy, they are often too large for real-time. We propose a lightweight RGB-T tracker built on MobileViT with a progressive fusion framework that models intra- and inter-modal interactions using separable mixed attention. This design delivers compact, effective features for accurate localization, with under 4M parameters and real-time performance of 25.7 FPS on the CPU and 122 FPS on the GPU, supporting embedded and mobile platforms. To the best of our knowledge, this is the first MobileViT-based multimodal tracker. Model code and weights are available in the GitHub repository.

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Mahdi Falaki, Maria A. Amer. 2025-06-23. Lightweight RGB-T Tracking with Mobile Vision Transformers. https://arxiv.org/abs/2506.19154

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