ImageNet-Sketch
Introduced by Wang et al. in Learning Robust Global Representations by Penalizing Local Predictive Power
ImageNet-Sketch data set consists of 50,889 images, approximately 50 images for each of the 1000 ImageNet classes. The data set is constructed with Google Image queries "sketch of ", where is the standard class name. Only within the "black and white" color scheme is searched. 100 images are initially queried for every class, and the pulled images are cleaned by deleting the irrelevant images and images that are for similar but different classes. For some classes, there are less than 50 images after manually cleaning, and then the data set is augmented by flipping and rotating the images.
Source: ImageNet-SketchBenchmarks
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Model soups
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CoCa
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µ2Net+
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Papers
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