OpenEvents V1：面向多模态事件定位的大规模基准数据集
OpenEvents V1: Large-Scale Benchmark Dataset for Multimodal Event Grounding
AI总结：
OpenEvents V1是一个大规模基准数据集，通过三个任务（事件感知图像描述、图像到新闻检索、文本到图像检索）促进多模态事件定位，包含20万篇文章和40万张图像，提供基线结果和评估协议。
摘要：
我们推出了OpenEvents V1，这是一个旨在推进以事件为中心的视觉-语言理解的大规模基准数据集。与专注于表面描述的传统图像描述和检索数据集不同，OpenEvents V1数据集通过三个主要任务强调上下文和时间定位：（1）生成丰富的、具有事件感知的图像描述，（2）从图像查询中检索与事件相关的新闻文章，以及（3）从叙事式文本查询中检索与事件相关的图像。该数据集包含来自CNN和《卫报》的超过20万篇新闻文章和40万张相关图像，涵盖不同领域和时间段。我们为所有任务提供了广泛的基线结果和标准化评估协议。OpenEvents V1为开发能够对复杂现实世界事件进行深度推理的多模态AI系统奠定了坚实基础。该数据集可在https://ltnghia.github.io/eventa/openevents-v1公开获取。
英文摘要：
We introduce OpenEvents V1a large-scale benchmark dataset designed to advance event-centric vision-language understanding. Unlike conventional image captioning and retrieval datasets that focus on surface-level descriptions, OpenEvents V1 dataset emphasizes contextual and temporal grounding through three primary tasks: (1) generating rich, event-aware image captions, (2) retrieving event-relevant news articles from image queries, and (3) retrieving event-relevant images from narrative-style textual queries. The dataset comprises over 200,000 news articles and 400,000 associated images sourced from CNN and The Guardian, spanning diverse domains and time periods. We provide extensive baseline results and standardized evaluation protocols for all tasks. OpenEvents V1 establishes a robust foundation for developing multimodal AI systems capable of deep reasoning over complex real-world events. The dataset is publicly available at https://ltnghia.github.io/eventa/openevents-v1.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
