CUB-200-2011 Dataset

The Caltech-UCSD Birds-200-2011 (CUB-200-2011) dataset is the most widely-used dataset for fine-grained visual categorization task. It contains 11,788 images of 200 subcategories belonging to birds, 5,994 for training and 5,794 for testing. Each image has detailed annotations: 1 subcategory label, 15 part locations, 312 binary attributes and 1 bounding box. The textual information comes from Reed et al.. They expand the CUB-200-2011 dataset by collecting fine-grained natural language descriptions. Ten single-sentence descriptions are collected for each image. The natural language descriptions are collected through the Amazon Mechanical Turk (AMT) platform, and are required at least 10 words, without any information of subcategories and actions.

Caltech-UCSD 鸟类200-2011（CUB-200-2011）数据集是细粒度视觉分类任务中最广泛使用的数据库。该数据库包含属于鸟类200个子类别的11,788张图片，其中5,994张用于训练，5,794张用于测试。每张图片都有详细的标注：1个子类标签、15个部位位置、312个二元属性和1个边界框。文本信息来源于Reed等人。他们通过收集细粒度自然语言描述来扩展CUB-200-2011数据集。为每张图片收集了10个单句描述。这些自然语言描述是通过Amazon Mechanical Turk（AMT）平台收集的，要求至少包含10个单词，且不得包含子类别和动作信息。