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English(EN) MOTOR: A Multimodal Dataset for Two-Wheeler Rider Behavior Understanding

新的MOTOR数据集旨在分析两轮车骑行者行为

研究人员推出了MOTOR数据集,这是一个新颖的多模态资源,旨在增进对两轮车骑行者行为的理解。该数据集包含超过25小时的多角度同步视频、骑行者眼动追踪数据、音频和遥测数据。它标注了交通情境、骑行者状态以及包括合法性标签在内的12种不同的骑行操作。 AI

影响 为开发和评估两轮车骑行者行为分析和安全系统的AI模型提供了基准。

排序理由 该集群描述了一个新的学术数据集和相关的基准研究。

在 arXiv cs.CV 阅读 →

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报道来源 [2]

  1. arXiv cs.CV TIER_1 English(EN) · Varun A. Paturkar, Shankar Gangisetty, C. V. Jawahar ·

    MOTOR: A Multimodal Dataset for Two-Wheeler Rider Behavior Understanding

    arXiv:2605.22550v1 Announce Type: new Abstract: Two-wheelers account for a disproportionately high share of road fatalities in the Global South. Research on two-wheeler rider behavior, however, lags far behind four-wheelers, where multimodal datasets have driven major advances in…

  2. arXiv cs.CV TIER_1 English(EN) · C. V. Jawahar ·

    MOTOR: A Multimodal Dataset for Two-Wheeler Rider Behavior Understanding

    Two-wheelers account for a disproportionately high share of road fatalities in the Global South. Research on two-wheeler rider behavior, however, lags far behind four-wheelers, where multimodal datasets have driven major advances in Advanced Driver Assistance Systems (ADAS). To a…