CFP: DLPR2016— a VALSE Special Event


The first International Workshop on Deep Learning for Pattern Recognition (DLPR 2016)

in conjunction with ICPR 2016

December 4, 2016. Cancun Center, Cancun, Q.Roo, Mexico


The major goal of this workshop is to provide a platform for researchers or graduate students around the world to share their progresses on deep learning for pattern recognition.


Paper Submission

Paper Submission must be written in English, with length between four and six double column pages adhering to the ICPR conference submission guidelines. The templates for 6 pages length Paper (A4 format) in Word or Latex can be downloaded from (

Submission is handled through the EasyChair system avaiable from here. Reviewing will be single-blind. In submitting a paper the authors acknowledge that no paper substantially similar in content has been or will be submitted elsewhere during the DLPR16 review period. Accepted papers that were presented at the workshop will be published via IEEE Xplore. Some of accepted papers will be invited to the Journal Special Issues of Pattern Recognition Letters (Elsevier) and Frontier of Computer Science (Springer).


Poster Submission

This workshop will follow the Vision And Learning SEminar (VALSE) fashion to invite posters. Authors of recent relevant papers published in highly selective international journals and conferences are encouraged to contribute in the poster session providing highlights of their work. Poster application is by e-mail to Workshop Chair at Accepted posters that were invited will be presented at the workshop. Authors of the invited posters do not have to pay any registration fee for this workshop, only required registering to the main conference of ICPR16


Important dates (tentative)

31 Aug. 2016               Paper submission deadline

15 Sep. 2016               Notification of paper acceptance

30 Oct. 2016               Poster submission deadline

7 Nov. 2016                Notification of poster acceptance

TBA 2016                 Camera-ready copy due

4 December 2016           Workshop


Scope and Topics

  • Deep learning architectures for pattern recognition
  • Optimization for deep learning
  • Sparse coding in deep learning
  • Transfer learning for deep learning
  • Deep learning for feature representation
  • Deep learning for facial analysis
  • Deep learning for object recognition
  • Deep learning for scene understanding
  • Deep learning for document analysis
  • Deep learning for dimension reduction
  • Deep learning for activity recognition
  • Deep learning for semantic segmentation
  • Deep learning for generative modeling
  • Deep learning for biometrics
  • Multi-modal deep learning
  • Performance evaluation of deep learning algorithms


Keynote Speakers



Workshop Chairs

Xiang Bai             Huazhong University Science and Technology

Zhaoxiang Zhang    Institute of Automation, Chinese Academy of Sciences

Shiguang Shan   Institute of Computing Technology, Chinese Academy of Sciences

Chunhua Shen                  University of Adelaide

Yi Fang            New York University Abu Dhabi and New York University

Jingdong Wang                 Microsoft Research Asia

Yangqing Jia                         Facebook

Shuicheng Yan              National University of Singapore