Heatmap regression
A short video describing heatmap regression using deep learning, and some example applications
What is heatmap regression?
As the name suggests, it’s basically the output of a regression spread over the spatial dimensions of an image. So rather than a binary output as in segmentation, the heatmap regression outputs one of a range of values, commonly between 0 and 1, for every pixel in the image.
The video explains this in more detail, along with some example applications and datasets (see the links below for links to the datasets).
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