A semi-supervised adaptation of narrative maps extracts visual storylines from historical photo archives and often beats random sampling on timelines of 10+ images, though the evaluation shares the expert who supplied labels.
In: Proceedings of the 22nd Conference on Computational Natural Language Learning
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Semi-Supervised Image-Based Narrative Extraction: A Case Study with Historical Photographic Records
A semi-supervised adaptation of narrative maps extracts visual storylines from historical photo archives and often beats random sampling on timelines of 10+ images, though the evaluation shares the expert who supplied labels.