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English(EN) CapStARE: Capsule-based Sequential Architecture for Robust and Efficient Gaze Estimation

新的胶囊架构提高了注视估计的准确性和速度

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了 CapStARE，一种用于注视估计的新型基于胶囊的架构。该系统利用冻结的 ConvNeXt 主干进行高效特征提取，并通过基于注意力的路由形成胶囊，以进行结构化的面部推理。它采用双 GRU 解码器进行轻量级序列建模，在 ETH-XGaze 和 MPIIFaceGaze 等基准数据集上实现了实时推理速度和强大的性能。 AI

影响 这种新架构为实时注视估计提供了一个实用且鲁棒的框架，有望改善人机交互和机器人应用。

排序理由 该集群包含一篇详细介绍注视估计新架构的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新的胶囊架构提高了注视估计的准确性和速度

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该集群包含一篇详细介绍注视估计新架构的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Miren Samaniego, Igor Rodriguez, Elena Lazkano ·

    CapStARE：基于胶囊的序列架构，用于鲁棒且高效的注视估计

    arXiv:2509.19936v2 Announce Type: replace Abstract: Human gaze estimation is essential for applications such as human-computer interaction, social robotics, and assistive systems. However, achieving accurate, interpretable, and real-time performance in unconstrained environments …

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