International Workshop on Fine Art Pattern Extraction and Recognition Call for Papers

FIRST CALL FOR PAPERS

International Workshop on Fine Art Pattern Extraction and Recognition
(FAPER 2020), 
Milan, Italy, September 18, 2020
https://sites.google.com/view/faper-workshop

In conjunction with the 
25th International Conference on Pattern Recognition (ICPR 2020), 
Milan, Italy, September 13-18, 2020
https://www.micc.unifi.it/icpr2020/

AIMS AND SCOPE

The cultural heritage, in particular fine art, has invaluable
importance for the cultural, historic and economic growth of our
societies. Fine art is developed primarily for aesthetic purposes and
it is mainly concerned with paintings, sculptures and
architectures. In the last years, due to technology improvements and
drastically declining costs, a large scale digitization effort has
been made, leading to a growing availability of large digitized fine
art collections. This availability, along with the recent advancements
in Pattern Recognition and Computer Vision, has opened new
opportunities to computer science researchers to assist the art
community with automatic tools to analyze and further understand fine
arts. Among the others, a deeper understanding of fine arts has the
potential to make them more accessible to a wider population, both in
terms of fruition and creation, thus supporting the spread of culture.

The ability to recognize meaningful patterns in fine art inherently
falls within the domain of human perception and this perception can be
extremely hard to conceptualize. Thus, visual-related features, such
as those automatically learned by deep learning models, can be the key
to tackle to problem of extracting useful representations from
low-level colour and texture features. These representations can
assist various art-related tasks, ranging from object detection in
paintings to artistic style categorization, useful for example in
museum and art gallery Websites.


The aim of the workshop is to provide an international forum for those
who wish to present advancements in the state-of-the-art, innovative
research, ongoing projects, academic and industrial reports on the
application of visual pattern extraction and recognition for a better
understanding and fruition of fine arts. The workshop solicits
contribution from diverse areas such as Pattern Recognition, Computer
Vision, Artificial Intelligence and Image Processing.

TOPICS

Topics of interest include, but are not limited to:

    Application of machine learning and deep learning to cultural heritage

    Computer vision and multimedia data

    Generative adversarial networks for artistic data

    Augmented and virtual reality for cultural heritage

    3D reconstruction of historical artifacts

    Historical document analysis

    Content-based retrieval in the art domain

    Speech, audio and music analysis from historical archives

    Digitally enriched museum visits

    Smart interactive experiences in cultural sites

    Projects, products or prototypes for cultural heritage
    restoration, preservation and fruition


SUBMISSION GUIDELINES 

Submissions must be formatted in accordance with the Springer's
Computer Science Proceedings guidelines
(https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines). Two
types of contribution will be considered:

    Full papers (12-15 pages, including references)

    Short papers (6-8 pages, including references)

Accepted manuscripts will be included in the ICPR 2020 Workshop
Proceedings Springer volume. Once accepted, at least one author is
expected to attend the event and orally present the paper. The
submission platform will be available soon.

IMPORTANT DATES

    Workshop submission deadline: June 15, 2020

    Workshop author notification: July 15, 2020

    Camera-ready submission: July 30, 2020

    Finalized workshop program: August 15, 2020

    Workshop day: September 18, 2020


CONTACTS

For any inquiry you may have, please send an email to Gennaro Vessio
at gennaro.vessio@uniba.it and Giovanna Castellano at
giovanna.castellano@uniba.it.