Datasets › STIR

STIR (Scaled and Translated Image Recognition)

Introduced by Thomas Altstidl et al. in Just a Matter of Scale? Reevaluating Scale Equivariance in Convolutional Neural Networks15 Nov 2022 archive 2025-07-28

While convolutions are known to be invariant to (discrete) translations, scaling continues to be a challenge and most image recognition networks are not invariant to them. To explore these effects, we have created the Scaled and Translated Image Recognition (STIR) dataset. This dataset contains objects of size s ∈[17, 64], each randomly placed in a 64 ×64 pixel image.

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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 2 papers for it but never published that list.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

Image Classification

License archive 2025-07-28

CC BY 4.0

Modalities archive 2025-07-28

Images

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

STIR

1 variant name, as the archive lists them.

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