8th Emotion Recognition in the Wild Challenge

March 6th, 2020 Daniela Lopez de Luise

Call for Challenge participation 

Eight Emotion Recognition in the Wild (EmotiW) Challenge 
https://sites.google.com/view/emotiw2020 

@ ACM International Conference on Multimodal Interaction 2020, Utretch, Netherlands 
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The Emotion Recognition in the Wild 2020 Challenge consists of multimodal classification challenges, which mimics real-world conditions. Traditionally, affect recognition has been performed on laboratory controlled data. While undoubtedly worthwhile at the time, such lab controlled data poorly represents the environment and conditions faced in real-world situations. With the increase in the number of video clips online, it is worthwhile to explore the performance of affect recognition methods that work ‘in the wild’.

Challenge sub-challenges:
1. Audio-video based Group Emotion Recognition 
2. Driver Gaze Prediction
3. Engagement prediction in the Wild
4. Physiological Signal based Emotion Recognition

Timeline:
Train and validate data available – 7th March 2020
Test data available – 1st June 2020
Paper submission deadline – July 2020
Paper notification – July 2020

Organisers: 
Abhinav Dhall, Monash University and IIT Ropar
Roland Goecke, University of Canberra 
Tom Gedeon, Australian National University 

 

Data Chairs:

Garima Sharma, Monash University

Yang Liu, Australian National University

 

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CVPR-WS: EarthVision 2020 – Large Scale Computer Vision for Remote Sensing Imagery [Extended Submission Deadline]

March 6th, 2020 Daniela Lopez de Luise

We are extending the submission deadline to March 16, 2020. More details below.

***************************
CALL FOR PARTICIPANTS & PAPERS

EarthVision 2020 – Large Scale Computer Vision for Remote Sensing Imagery Workshop in conjunction with CVPR 2020, 14th June 2020, Seattle, USA.

Website: https://www.grss-ieee.org/earthvision2020/

Earth Observation (EO) and remote sensing are fastly-growing fields of research where computer vision, machine learning, and signal/image processing meet. This workshop, held for its fourth edition at the CVPR 2020, aims at fostering collaboration between the computer vision as well as machine learning disciplines and the remote sensing community to boost automated interpretation of EO data.

We invite contributions in the fields of (not exhaustive list):
– Super-resolution in the spectral and spatial domain  
– Hyperspectral and multispectral image processing  
– 3D reconstruction from aerial images  
– Feature extraction and learning  
– Semantic classification of UAV / aerial and satellite images and videos  
– Deep learning tailored for Earth observation  
– Domain adaptation and concept drift  
– Human-in-the-loop  
– Multi-resolution, multi-temporal, multi-sensor, multi-modal processing  
– Public benchmark data sets: Training data standards, testing & evaluation metrics, as well as open source research and development.

CHALLENGE
Spanning three years while featuring five unique datasets and challenges, SpaceNet (https://spacenet.ai/) has continued to focus on different aspects of applying machine learning to solve difficult foundational mapping problems. Looking ahead to the EarthVision 2020 challenge, SpaceNet 6 will take us to a new frontier of data modality: Synthetic Aperture Radar (SAR). For the SpaceNet 6 challenge, participants will be asked to automatically extract building footprints with computer vision and artificial intelligence algorithms using SAR data.
The SpaceNet 6 challenge will run for approximately two months, running March 16 – May 1, 2020. The dataset may be found at https://spacenet.ai/rotterdam/.  
 
IMPORTANT DATES
Full paper submission:          March 16, 2020 (23:59 o'clock, PT)
Notification of acceptance:     April 07, 2020
Camera-ready paper:             April 16, 2020
Workshop (full day):            June 14, 2020

WORKSHOP ORGANIZERS
– Devis Tuia, Wageningen University, the Netherlands
– Jan Dirk Wegner, ETH Zurich, Switzerland
– Ronny Hänsch, German Aerospace Center, Germany
– Bertrand Le Saux, ONERA, France
– Naoto Yokoya, RIKEN, Japan
– Ilke Demir, DeepScale
– Nathan Jacobs, Uni. of Kentucky
– Krzysztof Koperski, Maxar
– Fabio Pacifici, Maxar
– Ramesh Raskar, MIT
– Myron Brown, John Hopkins University
– Mariko Burgin, NASA JPL

SPONSORING
The event is co-organized by the Image Analysis and Data Fusion (IADF) Technical Committee of the IEEE-GRSS, and it is sponsored by  
Gold sponsors: ESA (http://www.esa.int/), CosmiQ Works (http://www.cosmiqworks.org/),
Bronze sponsors: Kitware (https://www.kitware.com/).
 
Website: https://www.grss-ieee.org/earthvision2020/

See you soon!

On behalf of the organizing team,
Ronny Hänsch

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CollaborateCom 2020 and get high-quality reviewers, fair recognition, faster publishing with EAI Community Review

March 6th, 2020 Daniela Lopez de Luise

Web version


October 16-18, 2020 | Shanghai, People's Republic of China
Full Submission Deadline: March 31, 2020
sCOPE

The 16th International Conference on Collaborative Computing (CollaborateCom 2020) will be held in Shanghai, People’s Republic of China, and will continue to serve as a premier international forum for discussion among academic and industrial researchers, practitioners, and students interested in collaborative networking, technology and systems, and applications.

Future collaboration solutions that fully realize the promises of electronic collaboration require advancements in networking, technology and systems, user interfaces and interaction paradigms, and interoperation with application-specific components and tools.

CollaborateCom 2020 organizes special tracks to address the focused topics as follows: 

We are pleased to invite you to submit your paper to CollaborateCom 2020. Submissions should be in English, following the Springer formatting guidelines (see Submission). 

Read More: Call for Papers
Submit Paper

CollaborateCom authors have enjoyed over 213,000 downloads!
WORKSHOPs

CollaborateCom 2020 will hold following international workshops, seeking high-quality original research papers:

The SITN-2020 workshop is an international event, which aims to bring together expertise from academia and industry to build secure IoT infrastructures for smart society. It also provides a venue for international researchers and leading industry experts in IoT and cyber-security to establish future partnerships and research collaborations.

The CollaborateNet Workshop aims to facilitate all efforts for promoting the current network towards the content-centric future network using collaborative networking technologies. It could serve as a forum for researchers from academia and industry to exchange ideas, present new results, and provide prospective approaches towards future networks.

Workshop Paper Submission Deadline: March 31, 2020
EAI Community Benefits
Granting you visibility and fair review through
Community Review.
Get credits counting towards your EAI Index, membership ranks and global recognition.
Receive invaluable real-time feedback on your presentation on-site via EAI Compass.
Publication

All accepted and presented papers will be submitted for publishing by Springer and made available through SpringerLink Digital Library.

CollaborateCom proceedings will be submitted for indexing in leading indexing services, including Ei Compendex, ISI Web of Science, Scopus, CrossRef, Google Scholar, DBLP, as well as EAI’s own EU Digital Library (EUDL).

Authors of selected best accepted and presented papers will be invited to submit an extended version to:

And are also eligible for publication in:

Important dates

Full Paper Submission Deadline: March 31, 2020

Notification Deadline: June 12, 2020

Camera-ready deadline: July 15, 2020 

Conference dates: October 16 – 18, 2020
Follow us!

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HKUST(GZ): Founding Faculty in the Information Hub

March 6th, 2020 Daniela Lopez de Luise

The Hong Kong University of Science and Technology (Guangzhou Campus)

 

Founding Faculty in the Information Hub

The Hong Kong University of Science and Technology (HKUST) invites applications for founding faculty positions in Artificial Intelligence (AI) for its new campus in Guangzhou (GZ). HKUST(GZ) is interested in candidates at all ranks with a demonstrated ability to pursue high-impact research in AI and its applications. We specifically look for candidates interested in applied AI research, and are able to collaborate closely with domain experts in the target application areas to develop transformative technologies using AI. The initial focus areas include, but are not limited to, AI in design, AI in finance, AI in manufacturing, AI in medicine, AI in security and privacy, and AI in smart living. We welcome senior candidates to apply, especially those who can help with the strategic development of the AI trust area for the new Guangzhou campus.

 

Remuneration

HKUST(GZ) offers highly competitive salary of international standard and will be commensurate with qualifications and experience. Generous research funds, ample laboratory space and excellent research equipment and support will be provided. Housing allowances will also be provided.

 

Application Procedure

Applications should be sent to <gzrecruitINF@ust.hk> together with (i) full CV; (ii) a statement of research, teaching, and service; (iii) up to five most representative publications in PDF formats; (iv) record of teaching performance (if any); and (v) names and contact information of three referees. Applications will be evaluated as soon as they are received, and will receive full consideration until positions are filled. 

 

About the Information Hub

The HKUST(GZ) Information Hub focuses on addressing global challenges arising from human interactions with information and technology in an era of digital transformation. The Hub is mainly comprised of four thrust areas: Artificial Intelligence, Data Science and Analytics, Future Communication Networks, and Digital Media and Arts. We have also established an Internet of Things (IoT) division focused on technology transfer and industrial projects. In each of these areas, we are committed to providing a world-class education and conducting cutting-edge research with practical applications, with the purpose of not only advancing regional development but also making a global impact.

 

About HKUST Guangzhou Campus [https://gz.ust.hk/]

HKUST(GZ) offers a unique educational environment with four transdisciplinary hubs and 16 thrust areas. HKUST(GZ) offers superb research facilities, attracting top international faculty and students to conduct curiosity-driven and goal-oriented research to address the world’s pressing scientific and technological challenges.

HKUST(GZ) is situated in Nansha District, Guangzhou, which is right in the center of the Greater Bay Area, one of the most vibrant and dynamic regions in the world, neighboring Shenzhen, Hong Kong, and Macao. It is about 30 minutes away from Hong Kong by high-speed train. The new campus is under construction and is planned to open in 2022. The successful candidate may start working on the Clear Water Bay campus in Hong Kong before the new campus is completed.

pdf icon HKUST-GZ-Info-Hub-AI-Hiring-Ad.pdf
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Fwd: [C2020 workshop on “Fine Art Pattern Extraction and Recognition” (FAPER2020)

March 6th, 2020 Daniela Lopez de Luise

                          F A P E R   2 0 2 0

                    workshop in conjunction with the
    25th International Conference on Pattern Recognition (ICPR2020)
                  Milan, Italy, September 13-18, 2020

         >>> https://sites.google.com/view/faper-workshop/ <<<

              *** Submission deadline: June 15, 2020 ***

- Submission link: https://easychair.org/conferences/?conf=faper2020 -
_______________________________________________________________________

=== 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

=== 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. Authors of selected papers will be invited to extend and improve their contributions for a Special Issue of the Journal of Imaging (MDPI).

=== Important Dates ===

-  June 15th 2020 - workshop submission deadline
-  July 15th 2020 - author notification
-  July 30th 2020 - camera-ready submission
-  Aug. 15th 2020 - finalized workshop program
- Sept. 18th 2020 - workshop day

=== Organizing committee ===

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

=== Venue ===

The workshop will be hosted at Milan Congress Center (Mi.Co.), which is located in Piazzale Carlo Magno 1, Milan, 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/

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