PatternCom

PatternCom is a composed image retrieval benchmark based on PatternNet. PatternNet is a large-scale high-resolution remote sensing image retrieval dataset. There are 38 classes and each class has 800 images of size 256\u00d7256 pixels. In PatternCom, we select some classes to be depicted in query images, and add a query text that defines an attribute relevant to that class. For instance, query images of \u201cswimming pools\u201d are combined with text queries defining \u201cshape\u201d as \u201crectangular\u201d, \u201coval\u201d, and \u201ckidney-shaped\u201d. In total, PatternCom includes six attributes consisted of up to four different classes each. Each attribute can be associated with two to five values per class. The number of positives ranges from 2 to 1345 and there are more than 21k queries in total.