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RefCOCO+ 数据集是一个引用表达生成 (REG)数据集,用于理解引用图像中特定对象的自然语言表达的相关任务

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标注方式上: RefCOCOg采用的是非交互式标注法,选定区域请人标注,再请另外一批人根据标注的expression选择对应的region; RefCOCO和RefCOCO+采用的是双人游戏 (Refer it game)的方式. 数据划分方式上: RefCOCO和RefCOCO+包含train, val, testA, testB。testA的图片包含多个人;testB的图片包含多个除人之外的物体。同一个图片的object-expression样本对要么全在训练集,要么全在验证\测试集。 RefCOCOg包含train, val, test。是按照object进行划分的,同一个图片的object-expression样本对集合可能会在训练集一部分,在验证\测试集另一部分。 图片选择上: RefCOCO:图像包含同一类别的多个物体。 RefCOCO+:图像包含同一类别的多个物体,并且expression不能有绝对位置(e.g., left)的词。 RefCOCOg:图像包含同一类别的2-4个物体,覆盖面积超过图片面积的5%
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资源文件列表:

refcoco+.zip 大约有2个文件
  1. refcoco+/instances.json 114.63MB
  2. refcoco+/refs(unc).p 30.42MB
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RefCOCO 数据集是一个引用表达生成 (REG)数据集,用于理解引用图像中特定对象的自然语言表达的相关任务。以下是有关 RefCOCO 的关键细节: 收集方法:数据集是使用双人游戏ReferitGame收集的。在这个游戏中,第一个玩家查看带有分割目标对象的图像,并写出引用该对象的自然语言表达。第二个玩家只能看到图像和引用表达,并且必须单击相应的对象。如果两个玩家都表现正确,他们将获得积分并交换角色;否则,他们将收到一个新的对象和图像以供描述。 数据集变体: RefCOCO :包含 19,994 张图像中50,000个对象的 142,209 个引用表达式。RefCOCO +:包含 19,992 张图像中 49,856 个对象的 141,564 个表达式。RefCOCOg :此变体有 25,799 张图像、95,010 个引用表达式和 49,822 个对象实例。 语言和限制:RefCOCO 允许在引用表达式中使用任何类型的语言。RefCOCO+ 不允许在表达式中使用位置词,而应仅关注基于外观的描述(例如,“穿黄色圆点衬衫的男人”),而不是基于观察者的描述(例如,“左边第二个男人”
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