Global Sum Pooling: A Generalization Trick for Object Counting with Small Datasets of Large Images

28 May 2018 Shubhra Aich Ian Stavness

In this paper, we explore the problem of training one-look regression models for counting objects in datasets comprising a small number of high-resolution, variable-shaped images. We illustrate that conventional global average pooling (GAP) based models are unreliable due to the patchwise cancellation of true overestimates and underestimates for patchwise inference... (read more)

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