=== Aim & Scope ===

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 few 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 for computer science researchers to assist the art community with automatic tools to analyse and further understand fine arts. Among the other benefits, 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 tackling problems of extracting useful representations from low-level colour and texture features. These representations can assist in various art-related tasks, ranging from object detection in paintings to artistic style categorization, useful for examples 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, and academic and industrial reports on the application of visual pattern extraction and recognition for the better understanding and fruition of fine arts. The workshop solicits contributions 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- Historical document analysis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


=== Invited Speaker ===

Fabio Remondino (3DOM|FBK, Italy)

Dr. Fabio Remondino is the head of the 3D Optical Metrology (http://3dom.fbk.eu) research unit at FBK - Bruno Kessler Foundation (http://www.fbk.eu), a public research center located in Trento, Italy. His main research interests are in the field of reality-based surveying and 3D modeling, sensor and data fusion and 3D data classification. He is working in all automation aspects of the entire 3D reconstruction pipeline for applications in the industrial, environmental and heritage field. He is author of more than 200 articles in journals and conferences. He is involved in knowledge and technology transfer, organizing more than 30 conferences, 20 summerschools and 5 tutorials. Fabio is currently serving as President of the ISPRS Technical Commission II (http://www.isprs.org) and Vice-President of EuroSDR (http://eurosdr.net). He was vice-President of CIPA Heritage Documentation (https://www.cipaheritagedocumentation.org/) from 2015 to 2019.


=== Important Dates ===

- October 17th 2020 - workshop submission deadline (*EXTENDED*)
- November 10th 2020 - author notification
- November 15th 2020 - camera-ready submission
- December 1st 2020 - finalized workshop program


=== Submission Guidelines ===

Submissions must be formatted in accordance with the Springer's Computer Science Proceedings guidelines. The following paper categories are welcome:
- 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.

*** Due to the COVID pandemic, the workshop will be taken fully virtual. All accepted papers will be published. ***


=== FAPER 2020 Special Issue ===

Authors of selected papers will be invited to extend and improve their contributions in the Special Issue "Fine Art Pattern Extraction and Recognition" of the Journal of Imaging (MDPI).

- https://www.mdpi.com/journal/jimaging/special_issues/faper2020 -


=== Organizing committee ===

Gennaro Vessio (University of Bari, Italy)
Giovanna Castellano (University of Bari, Italy)
Fabio Bellavia (University of Palermo, Italy)

_________________________________________________________

Contacts: gennaro.vessio@uniba.it
giovanna.castellano@uniba.it
fabio.bellavia@unipa.it

Workshop: https://sites.google.com/view/faper-workshop/
ICPR2020: https://www.micc.unifi.it/icpr2020/