{"ID":2873215,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.09720","arxiv_id":"2509.09720","title":"Australian Supermarket Object Set (ASOS): A Benchmark Dataset of Physical Objects and 3D Models for Robotics and Computer Vision","abstract":"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.","short_abstract":"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...","url_abs":"https://arxiv.org/abs/2509.09720","url_pdf":"https://arxiv.org/pdf/2509.09720v1","authors":"[\"Akansel Cosgun\",\"Lachlan Chumbley\",\"Benjamin J. Meyer\"]","published":"2025-09-09T22:26:01Z","proceeding":"cs.CV","tasks":"[\"cs.CV\",\"cs.RO\",\"eess.IV\"]","methods":"[]","has_code":false}