---===== Apologies for cross-postings =====---
Please distribute this call to interested parties
________________________________________________________________________
International Workshop on Fine Art Pattern Extraction and Recognition
F A P E R 2 0 2 2
in conjunction with the 21st International Conference on
Image Analysis and Processing (ICIAP 2021)
Lecce, Italy, MAY 23-27, 2022
>>> https://sites.google.com/view/faper2022 <<<
*** Submission deadline: March 1, 2022 ***
-> Submission link: https://easychair.org/conferences/?conf=faper2022 <-
[[[ both virtual and in presence event ]]]
________________________________________________________________________
=== Aim & Scope ===
Cultural heritage, especially fine arts, plays an invaluable role in the
cultural, historical and economic growth of our societies. Fine arts are
primarily developed for aesthetic purposes and are mainly expressed
through painting, sculpture and architecture. In recent years, thanks to
technological improvements and drastic cost reductions, a large-scale
digitization effort has been made, which has led to an increasing
availability of large digitized fine art collections. This availability,
coupled with recent advances in pattern recognition and computer vision,
has disclosed new opportunities, especially for researchers in these
fields, to assist the art community with automatic tools to further
analyze and understand fine arts. Among 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.
Following the success of the first edition, organized in conjunction
with ICPR 2020, the aim of the workshop is to provide an international
forum for those wishing 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 a 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
and digital humanities
- Computer vision and multimedia data processing for fine arts
- Generative adversarial networks for artistic data
- Augmented and virtual reality for cultural heritage
- 3D reconstruction of historical artifacts
- Point cloud segmentation and classification for cultural heritage
- 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
- Visual question answering and artwork captioning
- Art history and computer vision
=== Invited speaker ===
Eva Cetinic (Digital Visual Studies, University of Zurich, Switzerland)
- "Beyond Similarity: From Stylistic Concepts to Computational Metrics"
Dr. Eva Cetinic is currently working as a postdoctoral fellow at the
Center for Digital Visual Studies at the University of Zurich. She
previously worked as a postdoc in Digital Humanities and Machine
Learning at the Department of Computer Science, Durham University, and
as a postdoctoral researcher and professional associate at the Ruđer
Boškovic Institute in Zagreb. She obtained her Ph.D. in Computer science
from the Faculty of Electrical Engineering and Computing, University of
Zagreb in 2019 with the thesis titled "Computational detection of
stylistic properties of paintings based on high-level image feature
analysis". Besides being generally interested in the interdisciplinary
field of digital humanities, her specific interests focus on studying
new research methodologies rooted in the intersection of artificial
intelligence and art history. Particularly, she is interested in
exploring deep learning techniques for computational image understanding
and multi-modal reasoning in the context of visual art.
=== Workshop modality ===
The workshop will be held in a hybrid form, both virtual and in presence
participation will be allowed.
=== Submission guidelines ===
Accepted manuscripts will be included in the ICIAP 2021 proceedings,
which will be published by Springer as Lecture Notes in Computer Science
series (LNCS). Authors of selected papers will be invited to extend and
improve their contributions for a Special Issue on IET Image Processing.
Please follow the guidelines provided by Springer when preparing your
contribution. The maximum number of pages is 10 + 2 pages for
references. Each contribution will be reviewed on the basis of
originality, significance, clarity, soundness, relevance and technical
content.
Once accepted, the presence of at least one author at the event and the
oral presentation of the paper are expected.
Please submit your manuscript through EasyChair:
https://easychair.org/conferences/?conf=faper2022
=== Important Dates ===
- Workshop submission deadline: March 1st 2022
- Author notification: March 10th 2022
- Camera-ready submission and registration: March 15th 2022
- Finalized workshop program: TBA
- Workshop day: TBA
=== Organizing committee ===
Gennaro Vessio (University of Bari, Italy)
Giovanna Castellano (University of Bari, Italy)
Fabio Bellavia (University of Palermo, Italy)
Sinem Aslan (University of Venice, Italy | Ege University, Turkey)
=== Venue ===
The workshop will be hosted at Convitto Palmieri, which is located in
Piazzetta di Giosue' Carducci, Lecce, Italy
____________________________________________________
Contacts: gennaro.vessio@uniba.it
giovanna.castellano@uniba.it
fabio.bellavia@unipa.it
sinem.aslan@unive.it
Workshop: https://sites.google.com/view/faper2022
ICIAP2021: https://www.iciap2021.org/
**********************************************************
*
* Contributions to be spread via DMANET are submitted to
*
* DMANET@zpr.uni-koeln.de
*
* Replies to a message carried on DMANET should NOT be
* addressed to DMANET but to the original sender. The
* original sender, however, is invited to prepare an
* update of the replies received and to communicate it
* via DMANET.
*
* DISCRETE MATHEMATICS AND ALGORITHMS NETWORK (DMANET)
* http://www.zaik.uni-koeln.de/AFS/publications/dmanet/
*
**********************************************************
Posts
