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Spatio-Temporal Action Localization datasets

archive 2025-07-28

6 datasets carry the task tag "Spatio-Temporal Action Localization" (the task itself: Spatio-Temporal Action Localization), ordered by the archive's paper count. Page 1 of 1: 6 shown of 6. 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

Spatio-Temporal Action Localization datasets 1–6 of 6

Kinetics (Kinetics Human Action Video Dataset)
The Kinetics dataset is a large-scale, high-quality dataset for human action recognition in videos.
1,341 papers · 18 benchmarks
AVA (Atomic Visual Actions)
AVA is a project that provides audiovisual annotations of video for improving our understanding of human activity.
113 papers · 7 benchmarks
Spatio-temporal action detection is an important and challenging problem in video understanding.
20 papers · 2 benchmarks
VidHOI is a video-based human-object interaction detection benchmark.
7 papers · 2 benchmarks
JRDB-Act is an extension of the JRDB dataset to create a large-scale multi-modal dataset for spatio-temporal action, social group and activity detection.
5 papers · 0 benchmarks
The LIRIS human activities dataset contains (gray/rgb/depth) videos showing people performing various activities taken from daily life (discussing, telphone calls, giving an item etc.).
1 paper · 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.