Datasets › VideoXum

VideoXum

Introduced by Jingyang Lin et al. in VideoXum: Cross-modal Visual and Textural Summarization of Videos21 Mar 2023 archive 2025-07-28

VideoXum is an enriched large-scale dataset for cross-modal video summarization. The dataset is built on ActivityNet Captions. The datasets includes three subtasks: Video-to-Video Summarization (V2V-SUM), Video-to-Text Summarization (V2T-SUM), and Video-to-Video&Text Summarization (V2VT-SUM).

Benchmarks archive 2025-07-28

All 1 leaderboard whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.

First row (archive order)PaperCode
Video Summarization videoxum VTSUM-BLIP 1 shot Micro-F1 23.5 VideoXum: Cross-modal Visual and Textural Summarization of Videos jylins/videoxum 1 Compare

Papers archive 2025-07-28

1 shown of 1 paper with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 8. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.

DateSamples run Syntology
VideoXum: Cross-modal Visual and Textural Summarization of Videos 1 1 21 Mar 2023 ran 1 of 1 samples (0 unverified; 1 pointer-only for licence)

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

No licence recorded in the archive. Absence here is not a statement about the dataset's terms.

Modalities archive 2025-07-28

Languages archive 2025-07-28

Variants archive 2025-07-28

  • VideoXum

1 variant name, as the archive lists them.

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