Highlight objects in image that need attention when driving with driver-gaze-yolov5
Highlight objects in image that need attention when driving with driver-gaze-yolov5
Where and What: Driver Attention-based Object Detection
arXiv paper abstract https://arxiv.org/abs/2204.12150v1
arXiv PDF paper https://arxiv.org/pdf/2204.12150v1.pdf
GitHub https://github.com/yaorong0921/driver-gaze-yolov5
Human drivers use their attentional mechanisms to focus on critical objects and make decisions while driving.
As human attention can be revealed from gaze data, capturing and analyzing gaze information has emerged in recent years to benefit autonomous driving technology.
Previous works in this context have primarily aimed at predicting “where” human drivers look at and lack knowledge of “what” objects drivers focus on.
… propose to integrate an attention prediction module into a pretrained object detection framework and predict the attention in a grid-based style.
Furthermore, critical objects are recognized based on predicted attended-to areas.
… achieves competitive state-of-the-art performance in the attention prediction on both pixel-level and object-level but is far more efficient (75.3 GFLOPs less) in computation.
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