Mouhamadou Sow


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SpatialVOC2K: A Multilingual Dataset of Images with Annotations and Features for Spatial Relations between Objects
Anja Belz | Adrian Muscat | Pierre Anguill | Mouhamadou Sow | Gaétan Vincent | Yassine Zinessabah
Proceedings of the 11th International Conference on Natural Language Generation

We present SpatialVOC2K, the first multilingual image dataset with spatial relation annotations and object features for image-to-text generation, built using 2,026 images from the PASCAL VOC2008 dataset. The dataset incorporates (i) the labelled object bounding boxes from VOC2008, (ii) geometrical, language and depth features for each object, and (iii) for each pair of objects in both orders, (a) the single best preposition and (b) the set of possible prepositions in the given language that describe the spatial relationship between the two objects. Compared to previous versions of the dataset, we have roughly doubled the size for French, and completely reannotated as well as increased the size of the English portion, providing single best prepositions for English for the first time. Furthermore, we have added explicit 3D depth features for objects. We are releasing our dataset for free reuse, along with evaluation tools to enable comparative evaluation.