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An Exploratory Study of Frequency-Aware Task Weighting for YOLOv8-Based Unified Driving Perception

arXiv · AI, language, vision and robotics · article · Aug 31, 2026 · UTC

Unified perception enables autonomous driving systems to perform object detection, drivable-area segmentation, and lane segmentation within a single network, improving efficiency and reducing deployment complexity. Jointly optimizing multiple perception tasks remains challenging because tasks exhibit different convergence rates, loss scales, and optimization stability. Existing task-weighting methods use loss magnitude, learned uncertainty, short-term loss changes, or gradient statistics; here, we explore the frequency structure of a recent loss-history window as a complementary signal. We imp

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