Dysfunction of the visual object recognition system in humans is briefly discussed and a basic connectionist model of visual object recognition is introduced. Experimentation in w...
Neil Davey, Ray J. Frank, Tim M. Gale, Stella J. G...
This paper provides a method for recognizing 3D objects in a single camera image and for determining their 3D poses. A model is trained solely based on the geometry information of ...
Markus Ulrich, Christian Wiedemann, Carsten Steger
Today's category-level object recognition systems largely focus on fronto-parallel views of objects with characteristic texture patterns. To overcome these limitations, we pr...
In this paper we address the problem of recognizing moving objects in videos by utilizing synthetic 3D models. We use only the silhouette space of the synthetic models making thus...
Alexander Toshev, Ameesh Makadia, Kostas Daniilidi...
We present a new unsupervised method to learn unified probabilistic object models (POMs) which can be applied to classification, segmentation, and recognition. We formulate this a...
Yuanhao Chen, Long Zhu, Alan L. Yuille, HongJiang ...