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Northwestern Polytechnical University
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MLLMs may signal hazards with over 95% accuracy, yet they struggle to identify the underlying causes, revealing a critical gap in proactive safety capabilities.
Ambient temperature fluctuations can be harnessed to create robust adversarial attacks that consistently deceive multimodal perception systems.
FUSION's innovative approach to integrating multi-cue features allows for robust tracking across diverse viewpoints, setting a new standard in pedestrian association and tracking.
