DualScope: Capturing Critical Spatial and Temporal Cues for Distracted Driving Activity Recognition
Zhijie Qiu, Shuaibo Li, Laixin Zhang, Xuming Hu, Wei Ma
Abstract
Accurately recognizing distracted driving activities in real-world scenarios is essential for improving road and pedestrian safety. However, existing approaches are prone to attending to irrelevant scene context and are susceptible to interference from redundant frames, compromising their robustness in complex driving environments. To overcome these limitations, we propose DualScope, a novel framework that captures behaviorally critical information from both spatial and temporal perspectives. In the spatial domain, we introduce a Synergistic Behavior-Centric Distillation mechanism that leverages two key information sources: (1) position-aware knowledge derived from the SAM model, which enhances the perception of critical regions and their semantic interaction structures; and (2) fine-grained visual details obtained from cropped key regions, which improve the model
BibTeX
@inproceedings{aaai2026_dualscopecapturi,
title = {DualScope: Capturing Critical Spatial and Temporal Cues for Distracted Driving Activity Recognition},
author = {Zhijie Qiu and Shuaibo Li and Laixin Zhang and Xuming Hu and Wei Ma},
booktitle = {AAAI 2026},
year = {2026}
}