Connectionists: Call for Papers: Big Data meets Computer Vision - A NIPS 2012 Workshop

[Samy Bengio]

*Big Data Meets Computer Vision: First International Workshop on Large
Scale Visual Recognition and Retrieval (BigVision 2012)

Held in conjunction with NIPS 2012. December 7 or December 8 (TBD), 2012.
Lake Tahoe, Nevada, USA.

https://sites.google.com/site/bigvision2012/

*
*=============
Overview
=============

The emergence of “big data” has brought about a paradigm shift throughout
computer science. Computer vision is no exception. The explosion of images
and videos on the Internet and the availability of large amounts of
annotated data have created unprecedented opportunities and fundamental
challenges on scaling up computer vision.

Over the past few years, machine learning on big data has become a thriving
field with a plethora of theories and tools developed. Meanwhile, large
scale vision has also attracted increasing attention in the computer vision
community. This workshop aims to bring closer researchers in large scale
machine learning and large scale vision to foster cross-talk between the
two fields. The goal is to encourage machine learning researchers to work
on large scale vision problems, to inform computer vision researchers about
new developments on large scale learning, and to identify unique challenges
and opportunities.

This workshop will focus on two distinct yet closely related vision
problems: recognition and retrieval. Both are inherently large scale. In
particular, both must handle high dimensional features (hundreds of
thousands to millions), a large variety of visual classes (tens of
thousands to millions), and a large number of examples (millions to
billions).

This workshop will consist of invited talks, panels, discussions, and paper
submissions. The target audience of this workshop includes industry and
academic researchers interested in machine learning, computer vision,
multimedia, and related fields.

**=============
**Call for Papers
**=============
**
*
*We invite high quality submissions of extended abstracts on topics
including, but not limited to

--State of the field: What really defines large scale vision? How does it
differ from traditional vision research? What are its unique challenges for
large scale learning?
--Indexing algorithms and data structures: How do we efficiently find
similar features/images/classes from a large collection, a key operation in
both recognition and retrieval?
--Semi-supervised/unsupervised learning: Large scale  data comes with
different levels of supervision, ranging from fully labeled and quality
controlled to completely unlabeled. How do we make use of such data?
--Metric learning: Retrieval visually similar images/objects requires
learning a similarity metric. How do we learn a good metric from a large
amount of data?
--Visual models and feature representations: What is a good feature
representation? How do we model and represent images/videos to handle tens
of thousands of fine-grained visual classes?
--Exploiting semantic structures: How do we exploit the rich semantic
relations between visual categories to handle a large number of classes?
--Transfer learning: How do we handle new visual classes
(objects/scenes/activities) after having learned a large number of them?
How do we transfer knowledge using the semantic relations between classes?
--Optimization techniques: How do we perform learning with training data
that do not fit into memory? How do we parallelize learning?
--Datasets issues: What is a good large scale dataset? How should we
construct datasets? How do we avoid dataset bias?
--Systems and infrastructure: How do we design and develop libraries and
tools to facilitate large scale vision research? What infrastructure do we
need?
--Submissions must be in NIPS 2012 format, with a maximum number of 4 pages
(excluding references).

The deadline of submission is 11:59pm PDT, September 16th, 2012.
Submissions do not have to be anonymous. Accepted papers will be presented
as oral talks or posters during the workshop. For detailed submission
instructions please visit https://sites.google.com/site/bigvision2012/

===============
Important Dates
===============

Submission deadline: September 16th, 2012.
Decision notification: October 7th, 2012.
Workshop date: December 7th or December 8th (TBD), 2012.

================
Confirmed Speakers
================

Alex Berg, Stony Brook University
Shih-Fu Chang, Columbia University
Andrew Ng, Stanford University
Florent Perronnin, Xerox Research Centre Europe
Lorenzo Torresani, Dartmouth College

==============
Organizers
==============

Samy Bengio, Google
Jia Deng, Stanford University
Fei-Fei Li, Stanford University
Yuanqing Lin, NEC Labs*

-- 
Samy Bengio | Research Scientist in Machine Learning | bengio at google.com |
http://bengio.abracadoudou.com
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