MIT-States

Introduced by Isola et al. in Discovering States and Transformations in Image Collections

The MIT-States dataset has 245 object classes, 115 attribute classes and ∼53K images. There is a wide range of objects (e.g., fish, persimmon, room) and attributes (e.g., mossy, deflated, dirty). On average, each object instance is modified by one of the 9 attributes it affords.

Source: Attributes as Operators: Factorizing Unseen Attribute-Object Compositions

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Benchmarks

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Task	Dataset Variant	Best Model
Image Retrieval with Multi-Modal Query	MIT-States	ComposeAE
Compositional Zero-Shot Learning	MIT-States	CANet
Compositional Zero-Shot Learning	MIT-States, generalized split	CAILA
Zero-Shot Learning	MIT-States	CZSL