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Multimodal Spatial Role Labeling @ CLEF 2017

11th September, 2017 - 14th September, 2017

The task of spatial role labeling (SpRL)[1] formalizes the spatial concepts and relations in the language to be mapped to qualitative spatial representation using machine learning.

The main goal of multi-modal SpRL is to explore the extraction of spatial information from two information resources that is image and text. This is important for various applications such as semantic search, question answering, geographical information systems and even in robotics for machine understanding of navigational instructions or instructions for grabbing and manipulating objects. It is also essential for some specific tasks such as text to scene conversion or vice-versa, scene understanding as well as general information retrieval tasks when using huge amount of available multimodal data from various resources. Moreover, there is an increasing interest in extraction of spatial information from medical images that are accompanied by natural language descriptions.


11th September, 2017
14th September, 2017


CLEF 2017
Dublin, Ireland