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Multimodal Abstractive Summarization for How2 Videos

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Figure

Figure 1: How2 dataset example with different modalities. “Cuban breakfast” and “free cooking video” is notmentioned in the transcript, and has to be derived from other sources.
Figure 2: Building blocks of the sequence-to-sequencemodels, gray numbers in brackets indicate which com-ponents are utilized in which experiments.
Figure 3: Word distribution in comparison with the hu-man summaries for different unimodal and multimodalmodels
Table A2: Example outputs of ground-truth text-and-video with hierarchical attention (8), text-only with ground-truth (5a), text-only with ASR output (5c), ASR output text-andv-video with hierarchical attention (9), actionfeatures with RNN (7) and action f

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