A multimodal multi-task architecture combining Mamba-based temporal-spatial features and task-specific gating achieves state-of-the-art accuracy on the AIDE assistive-driving benchmark at real-time speed.
Mmtl-uniad: A unified framework for multimodal and multi-task learning in assistive driving perception
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TEM^3-Learning: Time-Efficient Multimodal Multi-Task Learning for Advanced Assistive Driving
A multimodal multi-task architecture combining Mamba-based temporal-spatial features and task-specific gating achieves state-of-the-art accuracy on the AIDE assistive-driving benchmark at real-time speed.