§ 07 — Data & Code Open-source releases

Datasets, code,
benchmarks.
Open by default.

Reference implementations, benchmark datasets, and reproducible research releases from the Vidal Lab — including foundational releases like Hopkins 155 and ongoing migration to a centralized GitHub organization.

§ 07·1

Open-source releases

Three primary destinations.

Datasets

Vidal Lab Data

Datasets and benchmarks released by the lab — Hopkins 155, MHAD, JHU-ISI gestures, and others. Migration to the Vidal Lab GitHub organization is in progress.

  • Hopkins 155
  • MHAD
  • JHU-ISI Gestures
Reference code

Vidal Lab Code

Reference implementations for Generalized PCA, Sparse Subspace Clustering, Dual Principal Component Pursuit, dynamical-systems distances, and other lab methods.

  • GPCA
  • SSC
  • DPCP
GitHub

Vidal Lab on GitHub

Active code releases from the Vidal Lab organization on GitHub — projects, course materials, and reproducibility packages.

  • Active
  • Maintained
§ 07·2

Featured datasets

Foundational releases that have shaped the field.

Motion segmentation
A.

Hopkins 155

The benchmark for motion segmentation under affine and projective camera models — 155 sequences, point trajectories, ground truth.

2007 · widely cited
Action recognition
B.

MHAD

Multimodal Human Action Dataset — synchronized video, mocap, audio, accelerometer, and depth for actions across 12 subjects.

2013 · widely cited
Surgical AI
C.

JHU-ISI Gestures

The gold-standard dataset for surgical activity and skill assessment — robotic-surgery video paired with expert ratings.

2014 · widely cited
§ 07·3

Reference implementations

Algorithms with code released by the lab.

Building
on our work?

If you use our data or code, please cite the original papers — and we'd love to hear what you build. Issues and pull requests are welcome on GitHub.