Spatial pyramid matching (SPM) based pooling has been the dominant choice for state-of-
art image classification systems. In contrast, we propose a novel object-centric spatial
pooling (OCP) approach, following the intuition that knowing the location of the object of
interest can be useful for image classification. OCP consists of two steps:(1) inferring the
location of the objects, and (2) using the location information to pool foreground and
background features separately to form the image-level representation. Step (1) is …

A method is provided for classifying an image. The method includes inferring location
information of an object of interest in an input representation of the image. The method
further includes determining foreground object features and background object features from
the input representation of the image. The method additionally includes pooling the
foreground object features separately from the background object features using the location
information to form a new representation of the image. The new representation is different …