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We propose a novel image representation, termed Attribute-Graph, to rankimages by their semantic similarity to a given query image. An Attribute-Graphis an undirected fully connected graph, incorporating both local and globalimage characteristics. The graph nodes characterise objects as well as theoverall scene context using mid-level semantic attributes, while the edgescapture the object topology. We demonstrate the effectiveness ofAttribute-Graphs by applying them to the problem of image ranking. We benchmarkthe performance of our algorithm on the 'rPascal' and 'rImageNet' datasets,which we have created in order to evaluate the ranking performance on complexqueries containing multiple objects. Our experimental evaluation shows thatmodelling images as Attribute-Graphs results in improved ranking performanceover existing techniques.

Attribute-Graph: A Graph based approach to Image Ranking