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Tiny Anomalies

A novel benchmark for evaluating methods on the original, high-resolution image and ground-truth masks, focusing on segmentation performance as a function of the size of anomalies.

Data and Resources

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Cite this as

Alex Costanzino, Pierluigi Zama Ramirez, Giuseppe Lisanti, Luigi Di Stefano (2024). Dataset: Tiny Anomalies. https://doi.org/10.57702/6dbjtbbx

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It is available for use in manuscripts, and will be published when the Dataset is made public.

Additional Info

Field	Value
Created	December 3, 2024
Last update	December 3, 2024
Author	Alex Costanzino
More Authors	Pierluigi Zama Ramirez Giuseppe Lisanti Luigi Di Stefano
Homepage	https://arxiv.org/abs/2106.09541