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W01 – (CPPR 2018)
TBD

W02 –Computer Vision for Analysis of Underwater Imagery (CVAUI 2018)
The analysis of underwater imagery imposes a series of unique challenges, which need to be tackled by the computer vision community in collaboration with biologists and ocean scientists. We invite submissions from all areas of computer vision and image analysis relevant for, or applied to, underwater image analysis.

Organizers
Alexandra Branzan Albu, University of Victoria,
BC, Canada, aalbu@uvic.ca

Maia Hoeberechts, Ocean Networks Canada,
Victoria, BC, Canada, maiah@uvic.ca

Additional Information
Workshop URL(Website Link: http://cvaui2018.oceannetworks.ca)


W03 - Deep Learning for Pattern Recognition (DLPR 2018)
Deep Learning, which can be treated as the most significant breakthrough in the past 10 years in the field of pattern recognition and machine learning, has greatly affected the methodology of related fields like computer vision and achieved terrific progress in both academy and industry. It can be seen as a resolution to change the whole pattern recognition system. It achieved an end-to-end pattern recognition, merging the previous steps of pre-processing, feature extraction, classifier design and post-processing. It is expected that the development of deep learning theories and applications would further influence the field of pattern recognition. The major goal of this workshop is to provide a platform for researchers or graduate students around the world to report or exchange their progresses on deep learning for pattern recognition.

Organizers
Xiang Bai (Professor, Huazhong University Science and Technology); Yi Fang (Professor, New York University Abu Dhabi and New York University); Yangqing Jia (Research Lead and Manager, Facebook); Meina Kan (Associate Researcher, Institute of Computing Technology, Chinese Academy of Sciences); Shiguang Shan (Researcher, Institute of Computing Technology, Chinese Academy of Sciences); Chunhua Shen (Professor, University of Adelaide); Jingdong Wang (Researcher, Microsoft Research Asia); Gui-Song Xia (Professor, Wuhan University); Shuicheng Yan (Professor, National University of Singapore); Zhaoxiang Zhang (Professor, Institute of Automation, Chinese Academy of Sciences)

Additional Information

Workshop URL (Website Link: http://valser.org/DLPR/2018.htm)

W04 - 3rd International Workshop on Face and Facial Expression Recognition from Real-World Videos (FFER 2018)
The face plays a key role in many real-world applications such as security systems, human computer interaction, remote monitoring of patients, video annotation, and gaming. Having detected the face, pattern recognition techniques and machine learning algorithms are applied to facial images, for example, to find the identity of a subject or analyze her/his emotional status. Though face and facial expression recognition in still images and in ideal imaging conditions have been around for many years, they have been less explored in video sequences in uncontrolled real-world videos. Given the ubiquitous presence of video cameras, face and facial expression recognition from such videos is becoming increasingly important for many applications, for instance for security surveillance, remote patient monitoring. Recognizing faces and facial expressions from real-world videos, however, remain challenging because of low video quality, illumination variation, head pose variation, and significant occlusion. Despite these challenges, video offers dynamics and motion information that is not available in still image and they can be exploited to improve the recognition. The purpose of this workshop is to bring together researchers who are working on developing face and facial expression recognition systems that involve non-ideal conditions, like those that might be present in a real-world video.

Organizers
Kamal Nasrollahi (Aalborg University, Denmark); Gang Hua (Microsoft Research, USA); Thomas B. Moeslund (Aalborg University, Denmark); Qiang Ji (Rensselaer Polytechnic Institute, USA)

Additional Information

Workshop URL(Website Link: https://ffer.aau.dk/)

W05 - 7th IAPR International Workshop on Computational Forensics (IWCF 2018)
With the advent of high-end technology, fraudulent efforts are on rise in many areas of our daily life, may it be fake paper documents, forgery in the digital domain or copyright infringement. In solving the related criminal cases use of pattern recognition (PR) principles is also gaining an important place because of their ability in successfully assisting the forensic experts to solve many of such cases.
The 7th IAPR International Workshop on Computational Forensics (IWCF) will aim at addressing the theoretical and practical issues related to this field, i.e. role of PR techniques for analysing problems in forensics. Effort is to bring the people together who are working on these issues in different areas including document and speech processing, music analysis, digital security, forensic sciences, etc.

Organizers
Jean-Marc Ogier (University of La Rochelle, France); Chang-Tsun Li (Charles Sturt University, Australia); Nicolas Sidère (University of La Rochelle, France)

Additional Information
Workshop URL (Website Link: http://iwcf2018.univ-lr.fr)

W06 – (PREAI 2018)
TBD

W07 - ICPR Workshop on Pattern Recognition in Intelligent Financial Analysis and Risk Management (PRIFR 2018)
Recently, financial industry is featured with massive volumes of both structured and unstructured data, which are often associated with unlabeled and partially labeled data, or noisy and uncertain labels. Developing intelligent financial analysis and risk management tools for such data present major challenges for both practitioners and academic researchers. The proposed workshop mainly focuses on pattern recognition and machine learning methods such as kernel methods, feature selection, reinforcement learning, complex networks, deep learning methods, etc. for building intelligence for financial analysis and risk-based knowledge discovery.

Organizers
Lu Bai (Central University of Finance and Economics, Beijing, China); Jian Tang (HEC Montreal & Montreal Institute for Learning Algorithms (MILA), Canada); Luca Rossi (Department of Computer Science, Aston University, UK); Lixin Cui (Central University of Finance and Economics, Beijing, China)

Additional Information
Workshop URL (Website Link: https://cs.aston.ac.uk/icprprifr)

W08 – 2nd Workshop on Reproducible Research in Pattern Recognition (RRPR 2018)
Following the success of the first workshop Reproducible Research on Pattern Recognition that held at the previous ICPR event 2016, this event will propose a new edition in continuation of the previous event  with a new special focus on Digital Geometry and Mathematical Morphology. As for the previous edition, it is intended as both a participative short course on the basis of RR with open discussions with the attendants, and also as a practical workshop on how to do actual RR.

Organizers
Bertrand Kerautret (main chair); Miguel Colom; Bart Lamiroy; Daniel Lopresti; Pascal Monasse; Jean-Michel Morel; Hugues Talbot

Additional Information
Workshop URL (Website Link: https://rrpr2018.sciencesconf.org)

W09 - Sparse Representation in Image Processing (SRIP 2018)
Sparsity is the principle of representing a phenomenon with few elements. In signal/image processing, we say that a signal is sparse if most of its elements are zeros or nearly zeros. This principle of selecting "few elements" or dimensionality reduction is now necessary in almost all image processing and machine learning applications. It has been seen that clean natural signals/images are highly sparse after applying few transformations. This sparse decomposition plays a significant role in restoration from corrupted data and data compression. Sparsity lead to a dramatic improvement in the field of data compression, Image restoration, computer vision, noise rejection and other domains too.

Organizers
Mousumi Gupta (Sikkim Manipal Institute of Technology)

Additional Information
Workshop URL (Website Link:)

W10 - Visual observation and analysis of Vertebrate And Insect Behavior (VAIB 2018)
There has been an enormous amount of research on analysis of video data of humans, but relatively little on visual analysis of other organisms. The goal of this workshop is to stimulate and bring together the current research in this area, and provide a forum for researchers to share expertise. As we want to make this more of a discussion workshop, we encourage work-in-progress presentations. Reviewing will be lightweight and only abstracts will be circulated to attendees. The issues that the research will address include: detection of living organisms, organism tracking and movement analysis, dynamic shape analysis, classification of different organisms (eg. by species), assessment of organism behavior or behavior changes, size and shape assessment, counting, health monitoring, These problems can be applied to a variety of species at different sizes, such as fruit and house flies, crickets, cockroaches and other insects, farmed and wild fish, mice and rats, commercial farm animals such as poultry, cows and horses, and wildlife monitoring, etc. One aspect that they all have in common is video data.

Organizers
R. Fisher (Chair)(University of Edinburgh); J. Hallam (University of South Denmark); S. Palazzo (Universita' di Catania)

Additional Information
Workshop URL (Website Link: http://homepages.inf.ed.ac.uk/rbf/vaib18.html)

W11 - 5th International Workshop on Multimodal pattern recognition of social signals in human computer interaction (MPRSS 2018)
Building intelligent artificial companions capable to interact with humans in the same way humans interact with each other is a major challenge in affective computing. Such a type of interactive companion must be capable of perceiving and interpreting multimodal information about the user in order to be able to produce an appropriate response. The proposed workshop mainly focuses on pattern recognition and machine learning methods for the perception of the user’s affective states, activities and intentions.

Organizers
Friedhelm Schwenker (Ulm University, Germany); Stefan Scherer (University of Southern California, USA)

Additional Information
Workshop URL (Website Link: https://neuro.informatik.uni-ulm.de/MPRSS2018/)

W12 – (DLDAR 2018)
TBD

W13 - Multimedia Information Processing for Personality and Social Networks Analysis Workshop (MIPPSNA 2018)
The MIPPSNA 2018 workshop aims to compile the latest research advances on the analysis of multimodal information for facing problems that are not visually obvious, this is, problems for which the sole visual analysis is insufficient to provide a satisfactory solution. Specifically, two problems are of interest for the workshop: personality analysis and social behavior analysis, although submissions in related topics will be considered as well. The workshop is associated to an ICPR contest running two tracks in the same topics, see http://chalearnlap.cvc.uab.es/challenge/27/description/. Therefore, the workshop also accepts submissions from contest participants describing their solutions for the challenge.

Topics
All aspects of human behavior analysis in the context of social networks by using multimodal information. Including but not limited to gesture/action, emotion recognition, personality analysis and human-computer interaction.
Personality analysis from multimodal information. Including textual, visual, and audible information.
Information fusion for the analysis of human behavior in the context of social networks.
Information retrieval, categorization and clustering of social networks data, including images, text, and videos.
Analysis of human intention from social networks data involving multimodal information.
New tasks, data sets and benchmarks on human behavior analysis from multimodal information
Solutions and novel methodologies for approaching the tasks considered in the ICPR18 Multimedia Information Processing for Personality and Social Networks Analysis Contest

Organizers
Hugo Jair Escalante; Esaú Villatoro; Bogdan Ionescu; Gabriela Ramírez; Sergio Escalera; Martha Larson; Henning Müller

Additional Information
Workshop URL (Website Link: http://chalearnlap.cvc.uab.es/workshop/28/description/)