projectaria/aria-everyday-objects

Aria日常物品数据集是一个用于第一人称视角的3D物体检测的小型且具有挑战性的数据集。它由25个序列组成，总时长约45分钟，这些序列是在美国各地由非计算机视觉专家拍摄的。数据集中的每个序列都使用3D标注，包括相机校准、SLAM轨迹和SLAM半稠密点云辅助标注。共有1037个3D物体边界框实例，分为17个类别，包括床、椅子、沙发、门、地板、灯、镜子、植物、冰箱、屏幕、水槽、储物柜、桌子、墙壁、壁画、洗衣机/干衣机和窗户。该数据集旨在加速第一人称3D感知的研究。

Aria Everyday Objects (AEO) is a small, challenging 3D object detection dataset for egocentric data. It consists of approximately 45 minutes of egocentric data across 25 sequences captured by non-computer vision experts in a diverse set of locations throughout the US. Oriented 3D bounding boxes have been annotated for each sequence using camera calibration, SLAM trajectory, and SLAM semi-dense point cloud for assistance. There are 1037 instances of 3D object bounding boxes across 17 classes: Bed, Chair, Couch, Door, Floor, Lamp, Mirror, Plant, Refrigerator, Screen, Sink, Storage, Table, Wall, WallArt, WasherDryer, and Window. The dataset is designed to accelerate research in egocentric 3D perception.