mlsanityData to 14 Oct 2026

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

arXiv 2408.17207 ↗First posted 30 Aug 2024cs.CV cs.ROcited by 7

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Abstract (arXiv)

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.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 41 of its 54 references that are in the map. First posted on arXiv 30 Aug 2024.

Builds on

41 of 54 references.

References · 41

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29 more
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 5; 2026: 2.

7 papers.