Datasets › Florence3D

Florence3D

Introduced in Recognizing Actions from Depth Cameras as Weakly Aligned Multi-part Bag-of-Poses1 Jan 2013 archive 2025-07-28

The dataset collected at the University of Florence during 2012, has been captured using a Kinect camera. It includes 9 activities: wave, drink from a bottle, answer phone,clap, tight lace, sit down, stand up, read watch, bow. During acquisition, 10 subjects were asked to perform the above actions for 2/3 times. This resulted in a total of 215 activity samples.

Source: https://www.micc.unifi.it/resources/datasets/florence-3d-actions-dataset/ Image Source: https://www.micc.unifi.it/resources/datasets/florence-3d-actions-dataset/

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
Skeleton Based Action Recognition Florence 3D Deep STGC_K Accuracy 99.1% Spatio-Temporal Graph Convolution for Skeleton Based... — 7 Compare

Papers archive 2025-07-28

6 shown of 6 papers 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 18. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

Custom (research-only, non-commercial)

Modalities archive 2025-07-28

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • Florence 3D
  • Florence3D

2 variant names, as the archive lists them.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections