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<p>[Apologies if you receive multiple copies of this CfP]<br>
<br>
<b>*** Call for Papers for SUMAC 2021 ***</b><b><br>
</b><b>The 3rd workshop on Structuring and Understanding of
Multimedia heritAge Contents</b><b><br>
</b>In conjunction with ACM Multimedia 2021<br>
20-24 October 2020, Chengdu, China<br>
<br>
<b>Workshop:</b> <a class="moz-txt-link-freetext"
href="https://sumac-workshops.github.io/2021/">https://sumac-workshops.github.io/2021/</a>
<br>
<b>Conference:</b> <a class="moz-txt-link-freetext"
href="https://2021.acmmm.org">https://2021.acmmm.org</a> <br>
<br>
<b>*** Aims and scope</b><b><br>
</b><br>
The digitization of large quantities of analogue data and the
massive production of born-digital documents for many years now
provide us with large volumes of varied multimedia data (images,
maps, text, video, multi-sensor data, etc.), an important feature
of which is that they are cross-domain. "Cross-domain" reflects
the fact that these data may have been acquired in very different
conditions: different acquisition systems, times and points of
view. These data represent an extremely rich heritage that can be
exploited in a wide variety of fields, from Social Sciences and
Humanities to land use and territorial policies, including smart
city, urban planning, smart tourism and culture, creative media
and entertainment. In terms of research in computer science, they
address challenging problems related to the diversity and volume
of the media across time, the variety of content descriptors
(potentially including the time dimension), the veracity of the
data, and the different user needs with respect to engaging with
this rich material and the extraction of value out of the data.
These challenges are reflected in various research topics such as
multimodal and mixed media search, automatic content analysis,
multimedia linking and recommendation, and big data analysis and
visualization, where scientific bottlenecks may be exacerbated by
the time dimension, which also provides topics of interest such as
multimodal time series analysis.<br>
<br>
The objective of the third edition is to present and discuss the
latest and most significant trends in the analysis, structuring
and understanding of multimedia contents dedicated to the
valorization of heritage, with the emphasis on enabling access to
the big data of the past. We welcome research contributions for
the following (but not limited to) topics:<br>
<br>
- Multimedia and cross-domain data interlinking and recommendation<br>
- Dating and spatialization of historical data<br>
- Mixed media data access and indexing<br>
- Deep learning in adverse conditions (transfer learning, learning
with side information, etc.)<br>
- Multi-modal time series analysis, evolution modeling<br>
- Multi-modal & multi-temporal data rendering<br>
- Heritage - Building Information Modeling, Art<br>
- HCI / Interfaces for large-scale datasets<br>
- Smart digitization of massive quantities of data<br>
- Bench-marking, Open Data Movement<br>
- Generative modeling of cultural heritage<br>
<br>
<b>*** Important dates</b><b><br>
</b><br>
- Paper submission: 30 July 2021 (11:59 p.m. AoE)<br>
- Author acceptance notification: 26 August 2021<br>
- Camera-Ready: 2 September 2021<br>
- Workshop date: 20 or 24 October 2021 (TBA)<br>
<br>
<b>*** Submission guidelines</b><b><br>
</b><br>
Submission format. All submissions must be original work not under
review at any other workshop, conference, or journal. The workshop
will accept papers describing completed work as well as work in
progress. One submission format is accepted: full paper, which
must follow the formatting guidelines of the main conference ACM
MM 2021. Full papers should be from 6 to 8 pages (plus 2
additional pages for the references), encoded as PDF and using the
ACM Article Template. For paper guidelines, please visit: <a
class="moz-txt-link-freetext"
href="https://2021.acmmm.org/regular-papers">https://2021.acmmm.org/regular-papers</a>.<br>
<br>
Peer Review and publication in ACM Digital Library. Paper
submissions must conform with the “double-blind” review policy.
All papers will be peer-reviewed by experts in the field, they
will receive at least two reviews. Acceptance will be based on
relevance to the workshop, scientific novelty, and technical
quality. Depending on the number, maturity and topics of the
accepted submissions, the work will be presented via oral or
poster sessions. The workshop papers will be published in the ACM
Digital Library.<br>
<br>
<b>*** Organizers</b><b><br>
</b><br>
Valerie Gouet-Brunet (LaSTIG Lab / IGN - Gustave Eiffel
University, France)<br>
Margarita Khokhlova (Fujitsu France)<br>
Ronak Kosti (Pattern Recognition Lab / FAU Erlangen-Nurnberg,
Germany)<br>
Li Weng (Hangzhou Dianzi University, China)<br>
<br>
Looking forward to seeing you in Chengdu (virtually or not)! <br>
The workshop organizers</p>
<p><br>
</p>
<pre class="moz-signature" cols="72">--
Valerie Gouet-Brunet
Senior researcher / Directrice de recherche (DR1) du Ministère de l'Ecologie
LASTIG Lab.
Univ. Gustave Eiffel / IGN (French mapping agency)
73, Avenue de Paris - F94165 Saint-Mande CEDEX
Tel. +33 (0)1 43 98 62 10
<a class="moz-txt-link-freetext" href="https://www.umr-lastig.fr/vgouet/">https://www.umr-lastig.fr/vgouet/</a></pre>
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