We introduce Amazon Berkeley Objects (ABO), a new large-scale dataset designed to help bridge the gap between real and virtual 3D worlds. ABO contains product catalog images, metadata, and artist-created 3D models with complex geometries and physically-based materials that correspond to real, household objects. We derive challenging benchmarks that exploit the unique properties of ABO and measure the current limits of the state-of-the-art on three open problems for real-world 3D object understanding: single-view 3D reconstruction, material estimation, and cross-domain multi-view object retrieval.
翻译:我们引入了亚马逊伯克利天体(ABO),这是一个新的大型数据集,旨在帮助弥合真实和虚拟的3D世界之间的差距。ABO包含产品目录图像、元数据以及艺术家创建的3D模型,这些模型具有复杂的地貌和物理材料,与真实的、家用物体相对应。我们得出了具有挑战性的基准,利用ABO的独特性,衡量目前最新技术在现实世界3D天体理解的三个未决问题上的局限性:单视3D重建、材料估计和跨多视天体物体检索。