Day 1: Appearances

9:00 9:40 Shimon Edelman CBCL at MIT When a picture is worth (much) less than a thousand words
9:40 10:20 Michael J. Tarr Brown University Unifying theories of object recognition: Evidence that faces and the entry-level are not special
COFFEE
10:40 11:20 Amnon Shashua Hebrew Univeristy Multi-image coding and Tensor ranks
11:20 12:00 Roger Mohr Inria Rhones Alpes The advantage of image based representation of 3D objects
LUNCH
5:00 5:40 Bernt Schiele and James L. Crowley GRAVIR, INPG The Concept of Visual Classes
5:40 6:20 Baback Moghaddam MIT Media Lab A Baysian Framework for Appearance-Based Modeling
6:20 7:00 Pierre Jolicoeur Centre de Recherche en Neurosciences Cognitives Using brief masked displays to measure the orientation tuning of stored object representations

Day 2: Views, 3D models, Spatial Representations

9:00 9:40 Erik Granum Aalborg University CV and VR systems sharing models
9:40 10:20 Shmuel Peleg Hebrew University View Based Representations, Panoramic Mosaics by Manifold Projection
COFFEE
10:20 11:00 Heinrich H. Bulthoff Max-Planck Institut fur biologische Kybernetik View Based Representations, navigation and biological motion perception
11:20 12:00 Ilan Shimshoni Technion Visual Homing: Surfing on the Epipoles
LUNCH
5:00 5:40 Josef Kittler University of Surrey Shape Representation and Recognition Using Invariant Unary and Binary Relations
5:40 6:20 Yael Moses Weizmann Institute Modeling and recognizing 3D objects from single images using class-constraints
6:20 7:00 Claus Madsen Aalborg University Using view point planning to automatically obtain stable views of objects
7:00 7:20 Svante Barck-Holst and Stefan Carlsson KTH Visual Navigation using View Based Representations and Epipolar geometry

Day 3: Learning, invariants and statistics

9:00 9:40 Michael Werman Hebrew University On very simple representations
9:40 10:20 Ronen Basri Weizmann Institute View-Based Object Recognition
COFFEE
10:40 11:20 Luc Van Gool ESAT, University of Leuven Perceptual Organisation, Geometric structures for grouping: if you can't beat them, join them
11:20 12:00 Nathan Intrator Tel-Aviv University Natural goals for learning object representations
LUNCH
5:00 5:40 James Crowley INP Grenoble An Information Theory Approach to the Foundations of Computer Vision
5:40 6:20 Stefan Carlsson KTH Invariants, Views and Models
6:20 7:00 Daphna Weinshall Hebrew University Should model- view- and appearance- based approaches be distinguished?