升级版自拍视角数据集，增强动作与物体标注
NymeriaPlus: Enriching Nymeria Dataset with Additional Annotations and Data
- 在原始数据上增加密集3D/2D框标注和实例级三维重建
- 新增姿态数据格式、地图、音频与手环视频等多模态信息
- 适合研究具身智能的多模态学习与真实场景行为理解
Nymeria数据集于2024年发布，是大规模野外环境下多人活动的多视角可穿戴设备数据集，具有空间定位和时间同步特性。它包含动作捕捉服记录的体感真值、设备轨迹、半稠密3D点云及情境叙述。本文对Nymeria进行升级，提出NymeriaPlus，其包含：(1) 改进的动捕人体姿态数据，支持Momentum Human Rig (MHR) 和 SMPL 格式；(2) 室内物体与结构元素的密集3D与2D边界框标注；(3) 实例级别的3D物体重建；(4) 新增模态如基底地图记录、音频和腕带视频。通过整合这些互补模态与标注，NymeriaPlus将原始数据集提升为更强大的野外自拍视角基准。我们预期该数据集将填补现有自拍资源的关键空白，推动包括具身人工智能在内的多模态学习研究。
原文摘要 · Abstract (English)
The Nymeria Dataset, released in 2024, is a large-scale collection of in-the-wild human activities captured with multiple egocentric wearable devices that are spatially localized and temporally synchronized. It provides body-motion ground truth recorded with a motion-capture suit, device trajectories, semi-dense 3D point clouds, and in-context narrations. In this paper, we upgrade Nymeria and introduce NymeriaPlus. NymeriaPlus features: (1) improved human motion in Momentum Human Rig (MHR) and SMPL formats; (2) dense 3D and 2D bounding box annotations for indoor objects and structural elements; (3) instance-level 3D object reconstructions; and (4) additional modalities e.g., basemap recordings, audio, and wristband videos. By consolidating these complementary modalities and annotations into a single, coherent benchmark, NymeriaPlus strengthens Nymeria into a more powerful in-the-wild egocentric dataset. We expect NymeriaPlus to bridge a key gap in existing egocentric resources and to support a broader range of research, including unique explorations of multimodal learning for embodied AI.
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