Abstract: Authentication methods are disclosed for determining whether a person or object to be authenticated is a member of a set of authorized persons or objects. A query signature is acquired comprising a vector whose elements store values of an ordered set of features for the person or object to be authenticated. The query signature is compared with an aggregate signature comprising a vector whose elements store values of the ordered set of features for the set of authorized persons or objects. The individual signatures for the authorized persons or objects are not stored; only the aggregate signature. It is determined whether the person or object to be authenticated is a member of the set of authorized persons or objects based on the comparison. The comparing may comprise computing an inner product of the query signature and the aggregate signature, with the determining being based on the inner product.

Abstract: In a method for detecting an object in an input image, an input image vector representing the input image is generated by performing a regional maximum activations of convolutions (R-MAC) using a convolutional neural network (CNN) applied to the input image and using regions for the R-MAC defined by applying a region proposal network (RPN) to the output of the CNN applied to the input image. Likewise, a reference image vector representing a reference image depicting the object is generated by performing the R-MAC using the CNN applied to the reference image and using regions for the R MAC defined by applying the RPN to the output of the CNN applied to the reference image. A similarity metric between the input image vector and the reference image vector is computed, and the object is detected as present in the input image if the similarity metric satisfies a detection criterion.