Datasets › Two4Two

Two4Two (A Synthetic Dataset For Controlled Experiments)

Introduced by Leon Sixt et al. in Do Users Benefit From Interpretable Vision? A User Study, Baseline, And Dataset25 Apr 2022 archive 2025-07-28

Two4Two is a library to create synthetic image data crafted for human evaluations of interpretable ML approaches (esp. image classification). The synthetic images show two abstract animals: Peaky (arms inwards) and Stretchy (arms outwards). They are similar-looking, abstract animals, made of eight blocks. The core functionality of this library is that one can correlate different parameters with an animal type to create bias in the data.

Homepage JSON

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 1 paper for it but never published that list.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

Action Generation

License archive 2025-07-28

MIT

Modalities archive 2025-07-28

Actions

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

Two4Two

1 variant name, 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