We introduce a dataset containing human-authored descriptions of target locations in an "end-of-trip in a taxi ride" scenario. We describe our data collection method and a novel annotation scheme that supports understanding of such descriptions of target locations. Our dataset contains target location descriptions for both synthetic and real-world images as well as visual annotations (ground truth labels, dimensions of vehicles and objects, coordinates of the target location,distance and direction of the target location from vehicles and objects) that can be used in various visual and language tasks. We also perform a pilot experiment on how the corpus could be applied to visual reference resolution in this domain.
A disposable filter device having a plastic housing with inlet and outlet chambers separated by a filter disc sealed within the housing, the housing being readily disassemblable after use to remove the filter disc for identification or analysis of the material filtered from the fluid. Natural language descriptions of visual media present interesting problems for linguistic annotation of spatial information. This paper explores the use of ISO-Space, an annotation specification to capturing spatial information, for encoding spatial relations mentioned in descriptions of images. Especially, we focus on the distinction between references to representational content and structural components of images, and the utility of such a distinction within a compositional semantics. We also discuss how such a structure-content distinction within the linguistic annotation can be leveraged to compute further inferences about spatial configurations depicted by images with verbal captions.