Thanks to the wealth of high-quality annotated images available in popular repositories such as ImageNet, multimodal language-vision research is in full bloom. However, events, feelings and many other kinds of concepts which can be visually grounded are not well represented in current datasets. Nevertheless, we would expect a wide-coverage language understanding system to be able to classify images depicting recess and remorse, not just cats, dogs and bridges. We fill this gap by presenting BabelPic, a hand-labeled dataset built by cleaning the image-synset association found within the BabelNet Lexical Knowledge Base (LKB). BabelPic explicitly targets non-concrete concepts, thus providing refreshing new data for the community. We also show that pre-trained language-vision systems can be used to further expand the resource by exploiting natural language knowledge available in the LKB. BabelPic is available for download at http://babelpic.org.

Fatality Killed the Cat or: BabelPic, a Multimodal Dataset for Non-Concrete Concepts / Calabrese, Agostina; Bevilacqua, Michele; Navigli, Roberto. - (2020), pp. 4680-4686. (Intervento presentato al convegno Annual Meeting of the Association for Computational Linguistics tenutosi a Online).

Fatality Killed the Cat or: BabelPic, a Multimodal Dataset for Non-Concrete Concepts

Agostina Calabrese
;
Michele Bevilacqua
;
Roberto Navigli
2020

Abstract

Thanks to the wealth of high-quality annotated images available in popular repositories such as ImageNet, multimodal language-vision research is in full bloom. However, events, feelings and many other kinds of concepts which can be visually grounded are not well represented in current datasets. Nevertheless, we would expect a wide-coverage language understanding system to be able to classify images depicting recess and remorse, not just cats, dogs and bridges. We fill this gap by presenting BabelPic, a hand-labeled dataset built by cleaning the image-synset association found within the BabelNet Lexical Knowledge Base (LKB). BabelPic explicitly targets non-concrete concepts, thus providing refreshing new data for the community. We also show that pre-trained language-vision systems can be used to further expand the resource by exploiting natural language knowledge available in the LKB. BabelPic is available for download at http://babelpic.org.
2020
Annual Meeting of the Association for Computational Linguistics
multimodality; natual language processing; computer vision
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Fatality Killed the Cat or: BabelPic, a Multimodal Dataset for Non-Concrete Concepts / Calabrese, Agostina; Bevilacqua, Michele; Navigli, Roberto. - (2020), pp. 4680-4686. (Intervento presentato al convegno Annual Meeting of the Association for Computational Linguistics tenutosi a Online).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1431891
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