📄 中文摘要
EPRBench 是一个专门为基于事件流的视觉地点识别（VPR）设计的高质量基准数据集，旨在解决传统可见光摄像头在低光照、过曝和高速运动等挑战条件下的不稳定性。该数据集包含 10,000 个事件序列和 65,000 个事件帧，数据采集采用手持和车载设备，全面捕捉各种视角、天气条件和光照场景下的真实世界挑战。为支持语义感知和语言集成的 VPR 研究，EPRBench 提供了丰富的标注信息，促进相关领域的进一步发展。
EPRBench：一种高质量的基于事件流的视觉地点识别基准数据集
📄 English Summary
EPRBench: A High-Quality Benchmark Dataset for Event Stream Based Visual Place Recognition
EPRBench is a high-quality benchmark dataset specifically designed for event stream-based Visual Place Recognition (VPR), addressing the instability of conventional visible-light cameras under challenging conditions such as low illumination, overexposure, and high-speed motion. The dataset comprises 10,000 event sequences and 65,000 event frames, collected using both handheld and vehicle-mounted setups to comprehensively capture real-world challenges across diverse viewpoints, weather conditions, and lighting scenarios. To support semantic-aware and language-integrated VPR research, EPRBench provides rich annotation information, facilitating further advancements in the field.