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DeepVision 2014 : Deep Learning for Computer Vision

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Link: http://www.deep-vision.net
 
When Jun 28, 2014 - Jun 28, 2014
Where Columbus, Ohio
Submission Deadline Mar 15, 2014
Final Version Due May 15, 2014
Categories    machine learning   computer vision   pattern recognition
 

Call For Papers

The goal of the DeepVision Workshop 2014 is to accelerate the study of deep learning algorithms in computer vision problems. With the increase of acceleration of digital photography and the advances in storage devices over the last decade, we have seen explosive growth in the available amount of visual data and equally explosive growth in the computational capacities for image understanding. Instead of hand crafting features, recent advancement in deep learning suggests an emerging approach to extracting useful representations for many computer vision tasks. We encourage researchers to formulate innovative learning theories, feature representations, and end-to-end vision systems based on deep learning. We also encourage new theories and processes for dealing with large scale image datasets through deep learning architectures. We are soliciting original contributions that address a wide range of theoretical and practical issues including, but not limited to:

Supervised and unsupervised algorithms in computer vision,
Deep learning hardware and software architecture,
Advancements in deep learning,
Large scale computer vision problems including object recognition, scene analysis, industrial and medical applications.

Important Dates

Paper Submission (tentative): March 15th, 2014
Notification of acceptance: TBA,
Camera-ready paper: May 5th, 2014
Workshop (half day): 28th of June 2014

Paper Submission Information

The submission site is https://cmt.research.microsoft.com/DV2014/
The maximum paper length is 8 pages using the CVPR main conference format.
Submissions will be rejected without review if they contain more than 8 pages or violate the double-blind policy.

Workshop Chairs

Jose M. Alvarez, NICTA, Australia
Yann LeCun, NYU, USA
Fatih Porikli, (ANU/NICTA), Australia
Yi Li, NICTA, Australia

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