Background: Human observers can recognize three-dimensional objects seen in novel
orientations, even when they have previously seen only a relatively small number of different …

A general-purpose computer vision system must be capable of recognizing three-
dimensional (3-D) objects. This paper proposes a precise definition of the 3-D object …

Object recognition was studied in human subjects to determine whether the storage of the
visual objects was in a two-dimensional or a three-dimensional representation. Novel …

The recognition of 3-D objects from sequences of their 2-D views is modeled by a neural
architecture, called VIEWNET, that uses View Information Encoded With NETworks …

The problem of automatically learning object models for recognition and pose estimation is
addressed. In contrast to the traditional approach, the recognition problem is formulated as …

This paper presents results on appearance-based three-dimensional (3-D) object
recognition (3DOR) accomplished by utilizing a neural-network architecture developed …

You may have noticed, as I have, that the complexity of the visual system oscillates over
time. For quite a long time, centuries in fact, vision could call on rich internal representations …

An important problem in vision is to detect the presence of a known rigid, 3-d object. The
general 3-d object recognition task can be thought of as building a description of the object …

Previous results on nonlearnability of visual concepts relied on the assumption that such
concepts are represented as sets of pixels. The author uses an approach developed by …

In this paper we analyze the ability of a computer vision system to derive properties of the
three-dimensional (3-D) physical world from viewing two-dimensional (2-D) images. We …