Paper ID: 2408.17207

NanoMVG: USV-Centric Low-Power Multi-Task Visual Grounding based on Prompt-Guided Camera and 4D mmWave Radar

Runwei Guan, Jianan Liu, Liye Jia, Haocheng Zhao, Shanliang Yao, Xiaohui Zhu, Ka Lok Man, Eng Gee Lim, Jeremy Smith, Yutao Yue

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.

Submitted: Aug 30, 2024