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Video Summarization: Towards Entity-Aware Captions

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arxiv 2312.02188 v2 pith:4WDS5VVK submitted 2023-12-01 cs.CV cs.AIcs.CLcs.MM

Video Summarization: Towards Entity-Aware Captions

classification cs.CV cs.AIcs.CLcs.MM
keywords captionsvideonewsentity-awaretaskapproachcaptioningchallenging
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Existing popular video captioning benchmarks and models deal with generic captions devoid of specific person, place or organization named entities. In contrast, news videos present a challenging setting where the caption requires such named entities for meaningful summarization. As such, we propose the task of summarizing news video directly to entity-aware captions. We also release a large-scale dataset, VIEWS (VIdeo NEWS), to support research on this task. Further, we propose a method that augments visual information from videos with context retrieved from external world knowledge to generate entity-aware captions. We demonstrate the effectiveness of our approach on three video captioning models. We also show that our approach generalizes to existing news image captions dataset. With all the extensive experiments and insights, we believe we establish a solid basis for future research on this challenging task.

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