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NanoMVG: USV-Centric Low-Power Multi-Task Visual Grounding based on Prompt-Guided Camera and 4D mmWave Radar
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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.
Forward citations
Cited by 3 Pith papers
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Da Yu: Towards USV-Based Image Captioning for Waterway Surveillance and Scene Understanding
WaterCaption adds 20.2k waterway images with long, multi-region captions, and Da Yu with its Nano Transformer Adaptor produces competitive captions at a smaller computational cost.
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MetaOcc: Spatio-Temporal Fusion of Surround-View 4D Radar and Camera for 3D Occupancy Prediction with Dual Training Strategies
A multi-modal 3D occupancy prediction framework that fuses 4D radar and cameras, with height-aware radar features and hierarchical spatio-temporal fusion, achieving state-of-the-art results on OmniHD-Scenes and Surrou...
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RadarNeXt: Real-Time and Reliable 3D Object Detector Based On 4D mmWave Imaging Radar
A real-time 3D detector for 4D mmWave radar point clouds, built from a re-parameterizable MobileOne backbone and a deformable-convolution neck, achieves 50.48 mAP on VoD and 32.30 mAP on TJ4D.
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