论文标题
RP2K：用于细粒图像分类的大型零售产品数据集
RP2K: A Large-Scale Retail Product Dataset for Fine-Grained Image Classification
论文作者
论文摘要
我们介绍了RP2K，这是一种新的大规模零售产品数据集，用于细度图像分类。与以前关注相对较少产品的数据集不同，我们在属于2000种不同产品的货架上收集了500,000张零售产品的图像。我们的数据集旨在推进零售对象识别的研究，该零售对象识别具有大量的应用程序，例如自动货架审核和基于图像的产品信息检索。我们的数据集享有以下属性：（1）在产品类别方面，它是迄今为止最大的规模数据集。 （2）所有图像均在带有自然照明的物理零售商店中手动捕获，与真实应用的情况匹配。 （3）我们为每个对象提供丰富的注释，包括大小，形状和风味/气味。我们认为，我们的数据集可以使计算机视觉研究和零售行业受益。我们的数据集可在https://www.pinlandata.com/rp2k_dataset上公开获取。
We introduce RP2K, a new large-scale retail product dataset for fine-grained image classification. Unlike previous datasets focusing on relatively few products, we collect more than 500,000 images of retail products on shelves belonging to 2000 different products. Our dataset aims to advance the research in retail object recognition, which has massive applications such as automatic shelf auditing and image-based product information retrieval. Our dataset enjoys following properties: (1) It is by far the largest scale dataset in terms of product categories. (2) All images are captured manually in physical retail stores with natural lightings, matching the scenario of real applications. (3) We provide rich annotations to each object, including the sizes, shapes and flavors/scents. We believe our dataset could benefit both computer vision research and retail industry. Our dataset is publicly available at https://www.pinlandata.com/rp2k_dataset.
