Who Are You Referring To? Coreference Resolution In Image Narrations

Arushi Goel, Basura Fernando, Frank Keller, Hakan Bilen; Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2023, pp. 15247-15258

Abstract


Coreference resolution aims to identify words and phrases which refer to the same entity in a text, a core task in natural language processing. In this paper, we extend this task to resolving coreferences in long-form narrations of visual scenes. First, we introduce a new dataset with annotated coreference chains and their bounding boxes, as most existing image-text datasets only contain short sentences without coreferring expressions or labeled chains. We propose a new technique that learns to identify coreference chains using weak supervision, only from image-text pairs and a regularization using prior linguistic knowledge. Our model yields large performance gains over several strong baselines in resolving coreferences. We also show that coreference resolution helps improve grounding narratives in images.

Related Material


[pdf] [supp] [arXiv]
[bibtex]
@InProceedings{Goel_2023_ICCV, author = {Goel, Arushi and Fernando, Basura and Keller, Frank and Bilen, Hakan}, title = {Who Are You Referring To? Coreference Resolution In Image Narrations}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)}, month = {October}, year = {2023}, pages = {15247-15258} }