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Who are you referring to? Weakly supervised coreference resolution with multimodal grounding

IEEE International Conference on Computer Vision (ICCV), 2022
Abstract

Coreference resolution aims at identifying words and phrases which refer to same entity in a text, a core tool in natural language processing. In this paper, we propose a novel task, resolving coreferences in multimodal data, long-form textual descriptions of visual scenes. Most existing image-text datasets only contain short sentences without coreferent expressions, or coreferences are not annotated. To this end, we first introduce a new dataset, Flickr30k-Coref in which coreference chains and bounding box localization of these chains are annotated. We propose a new technique that learns to identify coreference chains through weakly supervised grounding from image-text pairs and a regularization using prior linguistic knowledge. Our model yields large performance gains over prior work in coreference resolution and weakly supervised grounding of long-form text descriptions.

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