Datasets › JTA

JTA (Joint Track Auto)

Introduced by Matteo Fabbri et al. in Learning to Detect and Track Visible and Occluded Body Joints in a Virtual World archive 2025-07-28

JTA is a dataset for people tracking in urban scenarios by exploiting a photorealistic videogame. It is up to now the vastest dataset (about 500.000 frames, almost 10 million body poses) of human body parts for people tracking in urban scenarios.

Source: Learning to Detect and Track Visible and Occluded Body Joints in a Virtual World

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
3D Human Pose Estimation JTA Dual network F1(t=0.4m) 58.15 Dual networks based 3D Multi-Person Pose Estimation from... 3dpose/3D-Multi-Person-Pose 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 36. 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
Dual networks based 3D Multi-Person Pose Estimation from Monocular Video 1 1 2 May 2022 not harvested

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

No language tagged.

Variants archive 2025-07-28

  • JTA

1 variant name, as the archive lists them.

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