1st International Workshop on Bridging the Gap between Semantics and Multimedia Processing (SeMP 2019)

Collocated with IEEE ISM 2019
San Diego, California, USA, December 9-11, 2019


The 1st International Workshop on Bridging the Gap Between Semantics and Multimedia Processing (SeMP 2019) workshop aims to bring together AI research in multimedia that can contribute to narrow or advance the understanding of the semantic gap that exists between multimedia signals and the concepts represented by these signals. This includes not only research that improves on traditional (symbolic or non-symbolic) AI techniques applied to multimedia, but also research that combines these techniques in novel, interesting, and experimental ways.

The workshop will provide a forum for researchers to present and discuss new ideas, work in progress, and preliminary results which can advance the state of current AI techniques and their interpretability applied to multimedia.

Topics of interest (not limited to)

  • Ontologies for multimedia and multimedia annotation
  • Hybrid/integrated representations of multimodal data and semantic descriptions
  • Concept detection and learning
  • Moving object detection, tracking, and description
  • Human intention detection and description
  • Multimedia understanding and summarization
  • Interactive scene description and interpretation
  • Probabilistic, non-monotonic reasoning over multimedia descriptions
  • Spatiotemporal query and reasoning over multimedia descriptions
  • Multi-sensorial and immersive media description
  • Real-time stream reasoning over multimedia data
  • Content- and concept-based multimedia understanding, modeling, management, and retrieval
  • Connectionist AI applied to multimedia (coding, communication, quality of experience, etc.)
  • Interpretability of deep-learning models for multimedia processing

The semantic gap

There is a big representational gap between the audiovisual signals that compose multimedia objects and the concepts represented by these signals. One way to narrow this gap, from the concepts side, is through symbolic AI. One can use logic to describe the multimedia content and then apply symbolic querying and reasoning to obtain relevant information from these descriptions. The problem with this purely symbolic approach is that it does not scale well.

The large volumes of multimedia data generated by current applications demand efficient methods of concept detection and annotation. This is where deep learning techniques usually come in—to narrow the gap from the signals side. Through deep learning one can learn correlations among the training dataset but overall it is not clear how these correlations map to high level semantic concepts, which brings many interpretability issues on current deep learning models. Additional challenges on both sides of the gap are posed by the diverse, multimodal, imprecise, and uncertain nature of multimedia data.

Submission and peer-review

Authors are invited to submit a 4-page manuscript in English in double-column IEEE format: Word, LaTeX, LaTeX (Bibliography Files). Authors must submit their PDF manuscripts through EasyChair.

At least two independent reviewers will evaluate each paper according to the suitability of its topic, originality, methodology, and clarity. The accepted papers will be presented at IEEE ISM 2019 and will be included in the conference proceedings.

Please only submit original material where copyright of all parts is owned by the authors declared and which is not currently under review elsewhere. See the IEEE policies for further information.

Accepted papers

  • Scoring Model of Figural Goodness and Its Application to Contour Completion Problems. Takahiro Hayashi and Koji Abe.
  • A CNN-based Tool to Index Emotion on Anime Character Stickers. Ivan Jesus, Jessica Cardoso, Antonio Busson, Alan Guedes, Ruy Milidiú, and Sérgio Colcher.
  • Knowledge Extraction through Multimedia Interpretive Trails in Educational Domain. Djefferson Smith Santos Maranhão, Antonio Carlos Raposo, Rodrigo Costa Mesquita Santos, Marcio Ferreira Moreno, Carlos de Salles Soares Neto, and Mário Antonio Meireles Teixeira.
  • Impact of Constant Visual Biofeedback on User Experience in Virtual Reality Exergames. Tanja Kojic, Lan Thao Nguyen, and Jan-Niklas Voigt-Antons.
  • Automatic Mapping Media to Device Algorithm that Considers Affective Effect. Sotaro Maejima, Yasuhiro Mochida, and Takahiro Yamaguchi.
  • Bridging the Gap between Semantics and Multimedia Processing. Marcio Ferreira Moreno, Guilherme Lima, Rodrigo Costa, Roberto Azevedo, and Markus Endler.

Important dates

  • Submission: October 14 October 18, 2019 23:59 PST
  • Acceptance notification: October 28, 2019
  • Camera-ready: October 31 November 8, 2019
  • Workshop: December 9-11, 2019

Organization and Program committee


Program committee:

  • Alan Livio, PUC-Rio, Brazil
  • Arkaitz Zubiaga, Queen Mary University of London, UK
  • Carlos Eduardo Batista, UFPB, Brazil
  • Carlos de Salles Soares Neto, UFMA, Brazil
  • Celso Alberto Saibel Santos, UFES, Brazil
  • Débora C. Muchaluat-Saade, UFF, Brazil
  • Edward Hermann Haeusler, PUC-Rio, Brazil
  • Fabio Marcos de Abreu Santos, Northern Arizona University‎, USA
  • Jack Jansen, CWI, The Netherlands
  • Joel Carbonera, UFRGS, Brazil
  • Joel dos Santos, CEFET/RJ, Brazil
  • Marcelo Moreno, UFJF, Brazil
  • Maria Da Graça Pimentel, USP, Brazil
  • Rafael Brandao, IBM Research, Brazil
  • Rudinei Goularte, ICMC-USP, Brazil
  • Sandro Fiorini, IBM Research, Brazil
  • Sergio Oramas, Universitat Pompeu Fabra, Spain
  • Sujan Perera, Amazon, USA
  • Sérgio Colcher, PUC-Rio, Brazil


The SeMP 2019 workshop will be collocated with IEEE ISM 2019, which will take place at the Wyndham San Diego Bay Side in San Diego, CA, USA. See the IEEE ISM 2019 website for more information on the venue.