NanoMVG: プロンプト誘導カメラと4Dミリ波レーダーによるUSV中心の低消費電力マルチタスク視覚グラウンディング
NanoMVG: USV-Centric Low-Power Multi-Task Visual Grounding based on Prompt-Guided Camera and 4D mmWave Radar
水上自律走行体（USV）向けに、カメラと4Dミリ波レーダーを自然言語で誘導し、物体の位置を特定する低消費電力マルチタスク視覚グラウンディングモデルNanoMVGを提案。WaterVGデータセットで競争力のある性能を示し、厳しい環境でも長時間運用可能。
著者: Runwei Guan, Jianan Liu, Liye Jia, Haocheng Zhao, Shanliang Yao, Xiaohui Zhu, Ka Lok Man, Eng Gee Lim, Jeremy Smith, Yutao Yue
分類: cs.CV, cs.RO
原文アブストラクト
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.
