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Dense Video Captioning datasets

archive 2025-07-28

9 datasets carry the task tag "Dense Video Captioning" (the task itself: Dense Video Captioning), ordered by the archive's paper count. Page 1 of 1: 9 shown of 9. Facet routes are this site's own (the archive records the tag string, not a page).

The archive holds 12,214 dataset rows; 12,172 are listed. 6 are withheld from every listing and count here as vandalised before snapshot (6 with contact-centre spam in the title, 0 with a spam description on a row that has no homepage, no paper and no papers counted; none with more than 1 paper, 0 with a benchmark), listed in withheld.json; 1 listed row carries a vandalised description, withheld on its page. This gate never withholds a row with a homepage or a paper that resolves, and a clean description; the content rules below withhold a row whose name is spam whatever else it carries. The gate is a phrase list: these are the rows it caught, not a claim that the rest is clean. Before that gate, the site's content rules withhold 36 more rows (invite-code, gambling, travel-booking, contact-centre and similar spam in the name or on a row with nothing real behind it); they have no page and are listed in withheld.json.

Filter 51 task tags shown of 3,717, by dataset count; the full filter by modality, task and language is on /datasets

Dense Video Captioning datasets 1–9 of 9

The ActivityNet Captions dataset is built on ActivityNet v1.3 which includes 20k YouTube untrimmed videos with 100k caption annotations.
255 papers · 6 benchmarks
YouCook2 is the largest task-oriented, instructional video dataset in the vision community.
198 papers · 7 benchmarks
This data set was prepared from 88 open-source YouTube cooking videos.
45 papers · 0 benchmarks
A new multitask action quality assessment (AQA) dataset, the largest to date, comprising of more than 1600 diving samples; contains detailed annotations for fine-grained action recognition, commentary generation, and estimating the AQA…
33 papers · 2 benchmarks
ViTT (Video Timeline Tags)
The ViTT dataset consists of human produced segment-level annotations for 8,169 videos.
14 papers · 2 benchmarks
VidChapters-7M is a dataset of 817K user-chaptered videos including 7M chapters in total.
5 papers · 4 benchmarks
Despite impressive advancements in video understanding, most efforts remain limited to coarse-grained or visual-only video tasks.
2 papers · 0 benchmarks
Procedural videos show step-by-step demonstrations of tasks like recipe preparation.
1 paper · 0 benchmarks
Vript (🎬 Vript: A Video Is Worth Thousands of Words)
We construct a fine-grained video-text dataset with 12K annotated high-resolution videos (~400k clips).
0 papers · 0 benchmarks

Paper counts and descriptions are the archive's, frozen 2025-07-28; no citation counts, no stars, no trending. Sorting by "most cited" or "newest" was a live-site feature the archive does not carry.