Counting with Focus for Free

Understand

This paper aims to count arbitrary objects in images.

• The leading counting approaches start from point annotations per object from which they construct density maps.
• Then, their training objective transforms input images to density maps through deep convolutional networks.
• We posit that the point annotations serve more supervision purposes than just constructing density maps.