Special Session on Deep Learning for Structured and Multimedia Information @ WCCI (IJCNN) 2018.

Chairs: Davide Bacciu (bacciu@di.unipi.it ), Silvio Jamil F. Guimarães and Zenilton K. G. Patrocínio Jr.

http://www.icei.pucminas.br/projetos/viplab/ijcnn-deepsm/

A key factor triggering the deep learning revolution has been its ground-breaking performance on image and video processing applications. These have been built mostly on a (multi-dimensional) raw data representation of the visual information. Multimedia content, on the other hand, calls for more articulated data representations catering for the multimodal nature of this information. These are often based on a structured representation that can capture the complexity of the contextual, semantic and geometrical relationships among the visual, phonetic and textual entities and concepts.

Scope and Topics:

The goal of this special session is to provide a forum for researchers working on the next generation of deep learning models for machine vision and multimedia information, which are capable of extracting and processing information in a structured representation and/or with a multimodal nature. We welcome contributions proposing innovative deep models dealing with:

• learning hierarchical or networked representations of multimedia information;
• processing of structured multimedia information under the form of sequences, labelled trees, as well as more general forms of graphs;
• understanding and synthesizing of multimodal data;
• fusion of multimodal information.

This special session is meant to attract researchers from deep learning, machine vision and multimedia information communities. We aim to bring together researchers with consolidated tradition on structured data processing (such as in machine learning and NLP) with those with machine vision and multimedia processing insight, but mostly working with flat-data representations.

Topics of interest for this special session include, but are not limited to, the following:

• deep learning models for structured data;
• representation learning in machine vision and multimedia processing;
• hierarchical/structured visual processing;
• deep models for visual data streams;
• generative and variational deep learning for multimedia data;
• multimedia data synthesis;
• attentional and bio-inspired models for the processing of visual and audio information;
• applied deep learning to machine vision and multimedia processing, such as: biomedical images and biobanks, pose and gesture estimation from graphs, etc.;
• innovative software and libraries for deep learning and multimedia content understanding.

Important dates:

• Paper Submission Deadline: 15 January 2018
• Paper Acceptance Notification Date: 15 March 2018
• Final Paper Submission and Early Registration Deadline: 1st May 2018
• IEEE WCCI 2018: 08-13 July 2018

This special session is supported by the IEEE Task Force on Deep Learning.

Conference Web Site