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SUMMARY The paper introduces a principled approach to generate a diverse set of relevant object proposals. This is formulated as optimizing a function F defined on sets of bounding boxes. This function is defined as a sum of a relevance term (which encourages individual bounding boxes to be likely to contain an object) and a diversity term. For optimization they commit to a greedy approach which iteratively adds the most promising bounding box, until the desired number of proposals was generated. The greedy procedure was motivated by existing theoretical guarantees on the obtained solution when F is submodular and monotone.