Call for paper
CVPR 2017 workshop on
DeepVision: Temporal Deep Learning (TDL)
http://deep-vision.net/
26 July 2017, Honolulu, Hawaii, USA

The computer vision community over the past few years has been dominated by deep learning based techniques. These techniques have, however, been mostly focused on still images, although many new publicly available data and high impact applications benefit from video recordings. Videos contain valuable temporal information that can be exploited to achieve better performance. Exploiting temporal information is of great importance in computer vision applications, like object tracking and recognition, scene analysis and understanding, etc. Deep learning based techniques are challenged to employ temporal information in such applications. Although some advances have been performed in this direction, mainly involving 3D convolutions, motion-based input features, or deep temporal- based models such as RNN-LSTM, significant advances are expected to be performed in this field. 
Papers on deep learning techniques utilizing temporal information on any of the following topics can be covered by the workshop:
TDL object recognition 
TDL object tracking 
TDL scene analysis 
TDL shape analysis 
TDL crowd analysis 
TDL human body motion analysis 
TDL facial analysis systems 
New TDL models 
New applications of TDL 


The submitted papers are limited to eight pages, including figures and tables, in the CVPR style. Additional pages containing only cited references are allowed. CVPR guidelines and templates given in the following page should be used:
http://cvpr2017.thecvf.com/submission/main_conference/author_guidelines

The accepted papers will be presented as posters at deep vision workshop and will be published in CVPR proceedings.

Important dates:

Submission deadline: March 31
Decision to authors: April 21
Camera ready: April 28
Submission through CMT at:
https://cmt3.research.microsoft.com/DV2017/


Organizing committee:
Kamal Nasrollahi (primary contact regarding paper submission: kn@create.aau.dk), Jose Alvarez Lopez, Sergio Escalera, Nathan Silberman, Ajmal Mian, Dhruv Batra, Gholamreza Anbarjafari, Yann LeCun , and Thomas B. Moeslund

Invited Speakers:
DeepVision:
Gabriel Kreiman
Sanja Fidler
Raia Hadsell
Hugo Larochelle
Lior Wolf
Temporal Deep Learning:
Maja Pantic
Trevor Darrell
Xiaogang Wang