Graphical Models for Scene Understanding:
|Overview||Call for Papers||IJCV special issue||Important Dates||Submission||Invited Speakers||Program||Committees|
Graphical models provide a ubiquitous modeling paradigm, which has been successfully employed up to now in a wide variety of computer vision tasks, including both low-level and high-level vision problems. Furthermore, due to their representational power, their modularity and (most importantly) due to their ability to efficiently capture dependencies or encode constraints, such models allow one to reason globally about an image or a scene. As such, they are expected to be of fundamental importance with regard to the task of natural scene understanding, which constitutes one of the central themes and goals of computer vision research.
This workshop will bring together experts in the areas of graphical models and scene understading, where its two main goals will be
The workshop will mostly consist of a selected set of invited talks given by experts in the field.
Furthermore, we invite the submission of original research contributions in computer vision and machine learning that present exciting recent developments or interesting new ideas related to the theme of the workshop. The topics may include but not limited to:
Paper submissions should consist of extended abstracts that are up to 4 pages long.
Organizers will invite full papers based on the submissions and workshop presentations. CFP to follow - will be open to further submissions of the community at large; all papers will be regularly reviewed.^ Top
|Submissions deadline:||September 7 (23:59 PDT)|
|Author notification:||October 1|
|Camera-ready papers:||October 12 (23:59 PDT)|
For submitting a paper, authors will need to create a user account at the workshop CMT paper submission site, which is located at the following URL: https://cmt.research.microsoft.com/GMSU2013/.
Submission formatting instructions are the same as the main ICCV conference, with the only difference being that a maximum number of 4 pages per paper applies in this case. The relevant LaTeX/Word templates can be downloaded from the ICCV website at this link.
|08:35||Invited talk: "Beyond MAP: Hedging Against Uncertainty via Multiple Diverse Predictions"||Dhruv Batra (Virginia Tech)|
|09:10||Invited talk: "Consistency Potentials: from Pairwise to Higher-order"||Stephen Gould (Australian National University)|
|09:45||"Multi-instance Object Segmentation with Exemplars"||Xuming He, Stephen Gould|
|10:30||Invited talk: "Modeling Complex Dependencies through Sequential Prediction"||Derek Hoiem (University of Illinois at Urbana-Champaign)|
|11:05||Invited talk: "Inference machines for scene understanding and recognition"||Martial Hebert (Carnegie Mellon University)|
|11:40||Invited talk: "Graphical models for interpreting shape"||Bill Freeman (MIT, CSAIL)|
Ecole des Ponts ParisTech, France
Universität Heidelberg, Germany
Universität Heidelberg, Germany
Bernt Schiele / Max
Planck Institut für Informatik, Saarbrücken, Germany
Stefan Roth / Technische Universität Darmstadt, Germany
Bjoern Ommer / Universität Heidelberg, Germany
Joerg Kappes / Universität Heidelberg, Germany
Tomas Werner / Czech Technical University, Czech Republic
Nikos Paragios / Ecole des Ponts ParisTech, France
Pawan Kumar / Ecole Centrale Paris, France
Stephen Gould / Australian National University, Australia
Dhruv Batra / Virginia Tech, USA
Derek Hoiem / University of Illinois at Urbana-Champaign, USA
Danny Tarlow / University of Toronto, Canada
Tamir Hazan / Toyota Technological Institute at Chicago, USA
George Papandreou / University of California, Los Angeles, USA
Amir Globerson / Hebrew University of Jerusalem, Israel
Alexander Schwing / ETH Zürich, Switzerland
Ofer Meshi / Hebrew University of Jerusalem, Israel