ASOS收录50种超市常见物品，提供高精度3D模型用于机器人与视觉任务评测。
Australian Supermarket Object Set (ASOS): A Benchmark Dataset of Physical Objects and 3D Models for Robotics and Computer Vision
- 从澳洲超市真实采购50种日常物品，构建可复现的物理对象数据集。
- 采用结构光重建技术生成50个完整纹理3D网格，覆盖10类不同形态。
- 适合做物体识别、位姿估计等实际场景下的算法验证，成本低易获取。
本文提出澳大利亚超市物品集（ASOS），一个包含50种可从主流澳洲超市购得的常见物品的基准数据集，配有高质量3D纹理网格，适用于机器人学与计算机视觉领域的评测。与依赖合成模型或难以获取的特殊物品的现有数据集不同，ASOS聚焦于真实、低成本、易获取的日常用品，涵盖10个不同类别，具有多样的形状、尺寸和重量。3D网格通过结构从运动（structure-from-motion）方法结合高分辨率成像获得，生成闭合无孔的网格模型。该数据集强调可访问性与现实应用价值，对物体检测、位姿估计及机器人任务的算法评估具有重要参考意义。
原文摘要 · Abstract (English)
This paper introduces the Australian Supermarket Object Set (ASOS), a comprehensive dataset comprising 50 readily available supermarket items with high-quality 3D textured meshes designed for benchmarking in robotics and computer vision applications. Unlike existing datasets that rely on synthetic models or specialized objects with limited accessibility, ASOS provides a cost-effective collection of common household items that can be sourced from a major Australian supermarket chain. The dataset spans 10 distinct categories with diverse shapes, sizes, and weights. 3D meshes are acquired by a structure-from-motion techniques with high-resolution imaging to generate watertight meshes. The dataset's emphasis on accessibility and real-world applicability makes it valuable for benchmarking object detection, pose estimation, and robotics applications.
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