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English(EN) SGAP-Gaze: Scene Grid Attention Based Point-of-Gaze Estimation Network for Driver Gaze

SGAP-Gaze网络利用场景注意力机制改进驾驶员注视点估计

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了SGAP-Gaze，一种新型的驾驶员注视点估计网络，该网络整合了面部和周围场景信息。该方法使用基于Transformer的注意力机制融合驾驶员面部和交通场景的特征，创建一个更全面的注视意图向量。与Urban Driving-Face Scene Gaze (UD-FSG)数据集上的现有方法相比，该模型显著降低了平均像素误差，证明了在真实驾驶场景中准确性的提高。 AI

影响 通过整合场景上下文提高了驾驶员注视点估计的准确性，可能增强驾驶员监控系统。

排序理由 这是一篇描述用于驾驶员注视点估计的新模型和数据集的研究论文。

在 Hugging Face Daily Papers 阅读 →

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SGAP-Gaze网络利用场景注意力机制改进驾驶员注视点估计

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报道来源 [1]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    SGAP-Gaze：基于场景网格注意力机制的驾驶员注视点估计网络

    Driver gaze estimation is essential for understanding the driver's situational awareness of surrounding traffic. Existing gaze estimation models use driver facial information to predict the Point-of-Gaze (PoG) or the 3D gaze direction vector. We propose a benchmark dataset, Urban…

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