Structured Query-Based Image Retrieval Using Scene Graphs

• URL: http://arxiv.org/abs/2005.06653v1
• Date: Wed, 13 May 2020 22:40:32 GMT
• Title: Structured Query-Based Image Retrieval Using Scene Graphs
• Authors: Brigit Schroeder, Subarna Tripathi
• Abstract summary: We present a method which uses scene graph embeddings as the basis for an approach to image retrieval. We are able to achieve high recall even on low to medium frequency objects found in the long-tailed COCO-Stuff dataset.
• Score: 10.475553340127394
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: A structured query can capture the complexity of object interactions (e.g. 'woman rides motorcycle') unlike single objects (e.g. 'woman' or 'motorcycle'). Retrieval using structured queries therefore is much more useful than single object retrieval, but a much more challenging problem. In this paper we present a method which uses scene graph embeddings as the basis for an approach to image retrieval. We examine how visual relationships, derived from scene graphs, can be used as structured queries. The visual relationships are directed subgraphs of the scene graph with a subject and object as nodes connected by a predicate relationship. Notably, we are able to achieve high recall even on low to medium frequency objects found in the long-tailed COCO-Stuff dataset, and find that adding a visual relationship-inspired loss boosts our recall by 10% in the best case.

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