Ego-1K：面向第一人称视觉的大规模多视角视频数据集
Ego-1K - A Large-Scale Multiview Video Dataset for Egocentric Vision
为第一人称多视角动态场景重建与4D新视角合成提供了一个时间同步、带标定的评测平台，其近距离动态物体与大视差设定可直接用于检验现有4D新视角合成方法在剧烈视差与自运动下的失效模式。
原文依据 Our experiments demonstrate that our dataset presents unique challenges for existing 3D and 4D novel view synthesis methods due to high disparities
摘要译文
由模型翻译 · 术语统一 · 请对照原文核对关键结论我们提出 Ego-1K，这是一个大规模、时间同步的第一人称多视角视频集合，旨在推动神经三维视频合成、动态场景理解与具身感知的发展。该数据集包含近 1,000 段短第一人称视频，由一套定制采集装置拍摄，该装置以 12 台同步相机环绕用户佩戴的 VR 头显。场景内容聚焦于不同环境下的手部运动与手物交互。我们描述了装置设计、数据处理与标定流程。该数据集为第一人称场景重建方法的基准评测提供了新途径。我们认为，随着配备多摄像头的智能眼镜日益普及，这是一个重要的研究领域。实验表明，由于近距离动态物体与装置自运动所导致的大视差与图像运动，该数据集对现有三维与四维新视角合成方法构成了独特挑战。该数据集可支撑这一挑战性领域的未来研究，并支持四维世界的创建与共享。
英文原文摘要 1007 字符
We present Ego-1K, a large-scale, time-synchronized collection of egocentric multiview videos designed to advance neural 3D video synthesis, dynamic scene understanding, and embodied perception. The dataset contains nearly 1,000 short egocentric videos taken with a custom rig with 12 synchronous cameras surrounding a VR headset worn by the user. Scene content focuses on hand motions and hand-object interactions in different settings. We describe rig design, data processing, and calibration. Our dataset enables new ways to benchmark egocentric scene reconstruction methods. We believe this is an important area of research as smart glasses with multiple cameras become omnipresent. Our experiments demonstrate that our dataset presents unique challenges for existing 3D and 4D novel view synthesis methods due to high disparities and image motion caused by close dynamic objects and rig egomotion. Our dataset supports future research in this challenging domain, enabling 4D world creation and sharing.