Subordinate-level categorization typically rests on establishing salient distinctions between part-level characteristics of objects, in contrast to basic-level categorization, whe...
Ryan Farrell, Om Oza, Ning Zhang, Vlad I. Morariu,...
We propose a more efficient privacy preserving set intersection protocol which improves the previously known result by a factor of O(N) in both the computation and communication c...
We present a manifold learning approach to dimensionality
reduction that explicitly models the manifold as a mapping
from low to high dimensional space. The manifold is
represen...
It is now common practice in machine vision to define the variability in an object's appearance in a factored manner, as a combination of shape and texture transformations. I...
Inspired by the underlying relationship between classification capability and the mutual information, in this paper, we first establish a quantitative model to describe the inform...