News Event Retrieval and Explanation from Large Collection of TV News Videos


News Event Retrieval and Explanation from Large Collection of TV News Videos (Proposal to be submitted)

The News Event Retrieval and Explanation Grand Challenge at ACM Multimedia 2025 is focused on retrieving, analyzing, and explaining news events from large-scale TV news video collections. 

The challenge features two evaluation modes: Interactive Mode (similar to VBS and LSC), where users refine queries and interact with the system, and Automatic Mode, where AI autonomously retrieves and explains news events. In Interactive Mode, the focus is on real-time human-AI collaboration, while Automatic Mode tests autonomous retrieval and reasoning. Both modes assess efficiency, accuracy, and scalability.

Participants will work with a large, multimodal dataset of TV news videos from various sources, including CNN, BBC, Reuters, and Vietnamese news channels. The dataset will include annotations such as speech transcriptions, OCR-extracted text, and temporal event timestamps. The challenge will use AI models for multimodal retrieval, video segmentation, and event explanation.

Organizers

Tentative Schedule

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