NanoMVG: USV-Centric Low-Power Multi-Task Visual Grounding based on Prompt-Guided Camera and 4D mmWave Radar
<|reference_start|>NanoMVG: USV-Centric Low-Power Multi-Task Visual Grounding based on Prompt-Guided Camera and 4D mmWave Radar: Recently, visual grounding and multi-sensors setting have been incorporated into perception system for terrestrial autonomous driving systems and Unmanned Surface Vehicles (USVs), yet the high complexity of modern learning-based visual grounding model using multi-sensors prevents such model to be deployed on USVs in the real-life. To this end, we design a low-power multi-task model named NanoMVG for waterway embodied perception, guiding both camera and 4D millimeter-wave radar to locate specific object(s) through natural language. NanoMVG can perform both box-level and mask-level visual grounding tasks simultaneously. Compared to other visual grounding models, NanoMVG achieves highly competitive performance on the WaterVG dataset, particularly in harsh environments and boasts ultra-low power consumption for long endurance.<|reference_end|>
@article{guan2024nanomvg:,
    title={NanoMVG: USV-Centric Low-Power Multi-Task Visual Grounding based on
  Prompt-Guided Camera and 4D mmWave Radar},
    author={Runwei Guan, Jianan Liu, Liye Jia, Haocheng Zhao, Shanliang Yao,
  Xiaohui Zhu, Ka Lok Man, Eng Gee Lim, Jeremy Smith, Yutao Yue},
    journal={arXiv preprint arXiv:2408.17207},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.17207},
    primaryClass={cs.CV cs.RO}
}