Workshop Image Analysis in Nuclear Research September, 2024, Prague, Czech Republic

July 23rd, 2024 Daniela Lopez de Luise

Dear  enthusiasts of computer vision and nuclear research,

we are delighted to invite you to the “Image Analysis in Nuclear Research” workshop, 

hosted by the Institute of Information Theory and Automation (ÚTIA), Prague, Czech Republic.

 

Event Details:

  • Date:                          September 9-11, 2024
  • Location:                   ÚTIA, Pod Vodarenskou vezi 4, Prague, Czech Republic
  • Registration:             Register Here
  • Further info :             WEB, leaflet

The workshop focuses on advanced image analysis in the context of nuclear research.

Topics Covered:

  • Nuclear Fuel Inspection
  • Image Processing
  • Neural Networks for Object Detection
  • 3D Point Cloud Acquisition and Representation
  • Micro-samples Analysis

Highlights:

  • Hands-on sessions
  • An excursion to the Research Center in Řež
  • Lectures from experts in nuclear research and digital image processing
  • Informal meetings

Important Dates:

  • Registration deadline:            July 31, 2024
  • Notification of acceptance:    first-come, first-served basis.  Register early to secure your spot!”

Objectives and Topics: This workshop offers a unique opportunity to delve into the methods of digital image processing used in nuclear research. You will learn about the applications of classical algorithms and the architectures of neural networks and AI shaping current nuclear research and industrial applications.

The keynote speakers for the workshop are from the following organizations: Research Centre Řež s.r.o. (CVŘ s.r.o.), Institute of Information Theory and Automation of the Czech Academy of Sciences (ÚTIA AV), Faculty of Mathematics and Physics, Charles University (MFF UK), and Institute of Physics of the Czech Academy of Sciences (FZÚ AV).

Registration: There is no registration fee. Luncheons, refreshments, and the evening dinner on the first day are provided free of charge. For an accommodation and transport, please contact us.

We look forward to your participation.

Sincerely,

Jan Blažek (blazek@utia.cas.cz) and Barbara Zitova (zitova@utia.cas.cz)

Neobsahuje žádné viry.www.avg.com

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WI-IAT’ 24 Call for Papers [Deadline Extended to 15 Aug 2024] !!!!!

July 23rd, 2024 Daniela Lopez de Luise

 

+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
                       CALL FOR PAPERS
        The 23rd IEEE/WIC International Conference on
   Web Intelligence and Intelligent Agent Technology (WI-IAT)
              December 9-12, 2024 | Bangkok, Thailand

    The key theme: Web Intelligence = AI in the Connected World
          A hybrid conference with both online and offline modes

        History of WI-IAT: www.youtube.com/watch?v=wOiSI3NhyKw
        Conference homepage: https://www.wi-iat.com/wi-iat2024/
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

Main Conference Papers Submission System:
https://wi-lab.com/cyberchair/2024/wi24/scripts/submit.php?subarea=WI

Workshops and Special Sessions Paper Submission:
https://wi-lab.com/cyberchair/2024/wi24/scripts/ws_submit.php?subarea=S

Keynote Speakers
++++++++++++++++++
Professor Danilo Mandic
Fellow of the Institute of Electrical and Electronics Engineering (IEEE)
President of the International Neural Network Society (INNS)
Imperial College, UK

Professor Ong Yew Soon
Fellow of the Institute of Electrical and Electronics Engineering (IEEE)
Nanyang Technological University, Singapore

Professor Guoyin Wang
Vice-President of the Chinese Association for Artificial Intelligence (CAAI)
President of Chongqing Normal University
Chongqing Normal University, China
Title: Brain Cognition Inspired Artificial Intelligence

More to be confirmed!

Sponsored By:
IEEE Computer Society
(IEEE-CS: https://www.computer.org/)
IEEE Computer Society Technical Committee on Intelligent Informatics
(TCII: https://www.computer.org/communities/technical-committees/tcii)
Web Intelligence Consortium
(WIC: https://wi-consortium.org/)
King Mongkut’s University of Technology Thonburi, Thailand
(KMUTT: https://www.kmutt.ac.th/en/)
Asia-Pacific Neural Network Society (APNNS)
IEEE-CIS Thailand Chapter

PAPER SUBMISSION GUIDELINE
++++++++++ ++++++++ ++++++++
Papers must be submitted electronically via CyberChair in standard IEEE Conference Proceedings format (max 8 pages, templates at https://www.ieee.org/conferences/publishing/templates.html).
Submitted papers will undergo a peer review process, coordinated by the International Program Committee.

The 2024 IEEE/WIC International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT'24) provides a premier international forum to bring together researchers and practitioners from diverse fields for presentation of original research results, as well as exchange and dissemination of innovative and practical development experiences on web intelligence and intelligent agent technology research and applications. Academia, professionals and industry people can exchange their ideas, findings and strategies in deepening the understanding of all Web's entities, phenomena, and developments in utilizing the power of human brains and man-made networks to create a better world and intelligent societies. More specifically, the fields of how artificial intelligence is impacting the Web of People, the Web of Data, the Web of Things, the Web of Trust, the Web of Agents, the Web in industry, society, health, and smart living, the Web of Everything, and emerging AIGC in WI-IAT.
Therefore, the theme of WI-IAT '24 will be:

“Web Intelligence = AI in the Connected World”.

WI-IAT '24 welcomes research and application paper submissions in these core thematic pillars under wider topics, which demand WI innovative and disruptive solutions for any of the next indicative sub-topics. Relevant topics include but are not limited to:

TRACKS AND TOPICS
++++++++++++++++++
TRACK 1: WEB OF PEOPLE
* Cognitive Modeling and Computing
* Conversational Search and Dialog Systems
* Crowdsourcing and Social Computing
* Human Centric Computing and Services
* Human Creativity and Decision-making Support
* Human-level Collective Intelligence
* Human-machine Co-intelligence in the Connected World
* Information Diffusion Modeling and Analysis
* Opinion Mining and Sentiment Analysis
* Recommendation Systems
* Situation and Personality Awareness
* Social Media and Social Networks
* User and Behavioural Modelling
* Wisdom Services

TRACK 2: WEB OF DATA
* Artificial Intelligence Generated Content (AIGC)
* Big Data Analytics and Deep Learning
* Big Data and Human Brain Complex Systems
* Cognitive Models and Computational Models
* Data Driven Services and Applications
* Data Integration and Data Provenance
* Data-Knowledge-Wisdom Hierarchy
* Data Science and Machine Learning
* Few-shot Learning and Transfer Learning
* Graph Isomorphism and Graph Theory
* Information Search and Retrieval
* Knowledge Graph and Semantic Networks
* Linked Data Management and Analytics
* Multimodal Data Fusion
* Large Language Models (LLMs) and Applications
* Representation Learning

TRACK 3: WEB OF THINGS
* Distributed Systems and Devices
* Dynamics of Networks
* Industrial Multi-domain Web
* Intelligent Ubiquitous Web of Things
* IoT Data Analytics
* Location and Time Awareness
* Open Autonomous Systems
* Sensor Networks
* Streaming Data Analysis
* Web Infrastructures and Devices Mobile Web
* Wisdom Web of Things

TRACK 4: WEB OF TRUST
* Blockchain Analytics and Technologies
* De-Platforming and No-platforming
* Decentralization of Internet
* Fake Content and Fraud Detection
* Hidden Web Analytics
* Monetization Services and Applications
* Trust Models for Agents
* Ubiquitous Computing
* Web Cryptography
* Web Safety and Openness
* Web-scale Security, Integrity, Privacy and Trust

TRACK 5: WEB OF AGENTS
* AI Agents and Multi-Agent Systems
* Autonomy Remembrance Agents
* Autonomy-oriented Computing
* Behaviour Modelling and Individual-based Modelling
* Chatbot and Intelligent Agent
* Computational Social Science
* Deep Reinforcement Learning
* Distributed Problem-Solving and Reasoning
* Edge Computing and Cloud Computing
* Local-global Behavioural Interactions
* Mechanism Design
* Network Autonomy Remembrance Agents
* Self-adaptive and Self-organizing Evolutionary Systems
* Social-cyber-physical Systems
* Symbols-Meaning-Value Space

SPECIAL TRACK: Web in Industry, Society, Education, Health and Smart Living, and the Web of Everything
* AIGC in Industry, Finance, Culture, Tourism, Education and Healthcare
* Data Brain, City Brain and Global Brain
* Data-driven Service Industry
* Data-driven Innovative Service-oriented Society
* Digital Ecosystems and Digital Epidemiology
* Digital Transformation and Digital Twin
* Generative AI and the Web of Everything
* Human-machine Symbiosis in a Connected World
* Web3, Metaverse and Smart Living
* Wellbeing and Healthcare in the 5G Era

SPECIAL TRACK in WI-IAT 2024: FAccT, LLM and AIGC
* Digital Divide, Fairness, Accountability, and Transparency
* Generative AI – LLM and AIGC
* Explainability and Interpretability
* Responsible AI
* Metric and Evaluation
* Applications and Use Cases
* Impact on Society
* Robustness and Security

IMPORTANT DATES
+++++++++++++++
July 30, 2024: Workshop Papers Submission
August 15, 2024: Papers Submission (Main Conference)
September 15, 2024: Paper Acceptance Notification (Main Conference)
September 15, 2024: Workshop Paper Acceptance Notification
December 9, 2024: Workshops and Special Sessions
December 10-11, 2024: Main Conference

Organization Structure
++++++++++++++++++++++
Honorary Chairs
* Irwin King, Chinese University of Hong Kong, Hong Kong, China
* Suvit Saetia, King Mongkut’s University of Technology Thonburi (KMUTT), Thailand

General Chairs
* Jonathan Chan, KMUTT, Thailand
* Ah-Hwee Tan, Singapore Management University, Singapore
* Yiyu Yao, University of Regina, Canada

Program Committee Chairs
* Kitsuchart Pasupa, KMITL, Thailand
* Sung-Bae Cho, Yonsei University, South Korea
* Mufti Mahmud, Nottingham Trent University, UK
* Haiqin Yang, International Digital Economy Academy, China

Local Organizing Chairs
* Nipon Charoenkitkarn, KMUTT, Thailand
* Phayung Meesad, KMUTNB, Thailand
* Kuntpong Woraratpanya, KMITL, Thailand
* Ruttikorn Varakulsiripunth, TNI, Thailand

Finance Chair
* Vajirasak Vanijja, KMUTT, Thailand

Workshop/Special Session Chairs
* Mark Chignell, University of Toronto, Canada
* Ashish Ghosh, Indian Statistical Institute, India
* Min Pan, Hubei Normal University, China
* Kaizhu Huang, Duke Kunshan University, China

Publicity Chairs
* Hongzhi Kuai, Maebashi Institute of Technology, Japan
* Susmita Ghosh, Jadavpur University, India
* Ka-Chun Wong, City University of Hong Kong, Hong Kong, China

Publication Chair
* Hongzhi Kuai, Maebashi Institute of Technology, Japan

Liaison Chair
* Sirawaj Itthipuripat, KMUTT, Thailand

WIC Steering Committee Chairs
* Ning Zhong, Maebashi Institute of Technology, Japan
* Jiming Liu, Hong Kong Baptist University, HK, China

WIC Executive Secretary
* Xiaohui Tao, University of Southern Queensland, Australia

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“Workshop on Advancing Non-invasive Human Motion Characterization in the Clinical Domain” (ANIMA) at BMVC

July 23rd, 2024 Daniela Lopez de Luise

Dear CVML community, we would like to share with you the call for papers for the:

 

1st Workshop on Advancing Non-invasive Human Motion Characterization in the Clinical Domain: Methods and Applications (ANIMA)

Workshop at BMVC, Glasgow, UK. 27th-28th November (exact date TBA)

https://anima2024.sites.uu.nl/

 

Motivation and topics

In the healthcare domain, understanding and characterizing human motion is essential for tasks, including diagnostics, monitoring and rehabilitation. Traditionally, the gold standard to accurately characterize and study human motion relies on motion capture systems and physical markers placed on the skin. These techniques are intrusive, expensive and they may limit natural movements. Furthermore, they limit the natural environment in which the analysis can take place. Recently, video analysis has become an increasingly viable alternative to marker-based systems to perform human motion analysis. This is due to the increasing progress – in terms of accuracy and computational resources needed – of deep learning algorithms in solving computer vision problems. In particular, recent advancements in deep learning-based Human Pose Estimation (HPE) algorithms enable the automated quantitative analysis of human motion from video data.

 

The application of computer vision in healthcare has the potential to revolutionize how we analyze human behavior. This workshop is positioned at the intersection of computer vision and medical applications, emphasizing the importance of extracting meaningful insights from video data. Our primary interest lies in the behavioral analysis of human motion. This focus is particularly crucial in healthcare, where precise understanding of an individual's movements can aid in early detection of neuromotor disorders, personalized care plans and effective rehabilitation strategies.

 

The medical domain poses unique challenges in ensuring robustness and high accuracy. Moreover, clinical applications require tailoring to specific demographics such as infants, elderly, or people with physical impairments. Consequently, dealing with data scarcity for training and benchmarking is another challenge. Our workshop aims to contribute to the broader computer vision community by focusing on those challenges that are inherent, but not unique, to the medical domain. We believe that tackling these topics in behavioral motion analysis within the medical domain will not only advance healthcare technology but also push the boundaries of computer vision research.

 

Topics of the workshop

  • Motion quantification: measurement of human pose and motion in 2D or 3D.
  • Motion classification: detection of specific human motions, training classifiers with limited data.
  • Clinical datasets: dealing with data scarcity, privacy, federated learning, synthetic data, and benchmarking.
  • Motion recording: use, calibration and combination of various sensors.
  • Applications: in the domain of infant analysis, diagnostics and rehabilitation.
  • Real-time analysis: algorithms to perform human motion analysis in real-time, enabling applications such as continuous monitoring in clinical settings.
  • Ethical considerations: studies that address ethical implications of using computer vision in healthcare, including issues related to privacy, consent and bias in algorithmic decision-making.

 

Invited speakers

Dr. Dimitris Tzionas is an assistant professor at the University of Amsterdam. He conducts research on the intersection of Computer Vision, Computer Graphics and Machine Learning. His motivation is to understand and model how people look, move and interact with the physical world and with each other to perform tasks. This involves: (1) accurately “capturing” real people and their whole-body interactions with scenes and objects, (2) modeling their shape, pose and interaction relationships, (3) applying these models to reconstruct real-life actions in 3D/4D and (4) using these models to generate realistic interacting avatars in 3D/4D. Potential applications include Ambient Intelligence, Virtual Assistants, Human-Computer/Robot Interaction and Mixed Reality. The long-term goal is to develop human-centered AI that perceives humans, understands their behavior and helps them to achieve their goals.

 

Dr. Logan Wade is a Research Fellow at the University of Bath, United Kingdom. As a clinical biomechanist, his research harnesses computer vision and machine learning to identify how patients move, with the goal of integrating biomechanical measures into clinical practice. Recent advances in Artificial Intelligence has seen the rise of motion capture methods that are fast and minimally invasive, allowing collection of data in clinics that was previously restricted to high-end biomechanical laboratories. However, while the accuracy of these systems has drastically improved over the past decade, determining if their accuracy is sufficient for use on an individual patient level is still to be determined. His long-term goal is to develop computer vision tools that are clinically relevant, employing mediums such as markerless video capture to identify movements of the body and 3D ultrasound to examine patient-specific spinal postures.

 

Dr. Sara Moccia is an Associate Professor in bioegineering at Universit`a degli Studi G. d’Annunzio (Chieti, Italy). She works on designing AI algorithms for clinical data analysis, with a specific focus on preterm infants’ care. She is the author of more than 50 papers. She is PI for three research projects for a total budget of around 2 mln euro. She serves as Associate editor for two international journal and currently as program chair for IPCAI

 

Dr. Simona Tiribelli is the director for AI Ethics of the Institute for Technology & Global Health at the MIT-funded spin-off PathCheck Foundation (Boston, US), assistant professor at the University of Macerata (Italy), where she teaches Ethics of Artificial Intelligence and Global Justice and Technology, 2023 visiting scholar in AI ethics at the New York University (NYU), and 2020 Fulbright awarded and fellow at the MIT Media Lab, Massachusetts Institute of Technology, US. She is also a founder of the spin-off GAIA (AI Ethics and Governance) and AI Ethics advisor for companies in Europe and US. She authored two books and a number of articles in leading scientific international journals on ethics of artificial intelligence and digital technology, and delivered on invite more than 50 talks in academic institutions such as Harvard University, Tufts University, Toronto University, and many more, in Europe, Canada, and USA.

 

Important dates

Paper submission: August 25th, 2024

Notification of acceptance: September 8th, 2024

Camera-ready submission: September 16th, 2024

 

Submission

Workshop papers should adhere to the paper guidelines of the main conference: https://bmvc2024.org/authors/author-guidelines/ Accepted papers will be included in the BMVC workshop proceedings published and DOI-indexed by BMVA. Submissions can be made through the submission system: TODO

 

Organizers

Lucia Migliorelli: Department of Information Engineering, Marche Polytechnic University, Italy, l.migliorelli@staff.univpm.it

Matteo Moro: Department of Informatics, Bioengineering, Robotics and Systems Engineering (DIBRIS), University of Genova & Machine Learning Genoa (MaLGa) Center, Genova, Italy, matteo.moro@unige.it

Ronald Poppe: Department of Information and Computing Sciences, Utrecht University, Utrecht, The Netherlands, r.w.poppe@uu.nl

 

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SOFSEM 2025 Call for papers

July 23rd, 2024 Daniela Lopez de Luise
                   *************************
                   ****   SOFSEM 2025   ****
50th International Conference on Current Trends in Theory and Practice of Computer Science
            January 20 – 23, 2025, Bratislava, Slovakia
                      
                       http://www.sofsem.sk
                         Call for Papers
SOFSEM is an annual winter conference devoted to the theory and practice of
computer science. The conference traditionally focuses on the latest results
and developments of fundamental research in computer science (informatics),
inspired by the algorithmic challenges of our time. SOFSEM has a long tradition
as a high-quality research conference, and a venue where researchers from
academia and industry in all stages of their career can share their insights.
The series of SOFSEM conferences began in 1974, and was only interrupted in
2022 due to the covid pandemic. In 2025, at its 50th edition, SOFSEM will be
held as a physical event in Bratislava, Slovakia. The proceedings will be
published in the subseries ARCoSS (Advanced Research in Computing and Software
Science) of the Lecture Notes in Computer Science (LNCS) of Springer.
Topics
The program committee encourages submission of original research papers in all
areas of foundations of computer science and artificial intelligence, including
e.g.
 * AI-based algorithms and techniques,
 * algorithms (approximation, combinatorial, exact, online, parameterized, probabilistic, 
   streaming, etc)
 * automata (cellular, finite, networked, etc), languages, machine models, rewriting systems
 * computability, decidability, classical and non-classical models of computation,
 * computational complexity (incuding e.g. communication, descriptional, fine-grained, 
   Kolmogorov, non-uniform, fixed-parameter and structural complexity),
 * computational geometry,
 * computational learning,
 * cryptographic techniques and security,
 * data compression algorithms,
 * data- and pattern mining methods (includeing e.g. models, theory, algorithms)
 * discrete combinatorial optimization, heuristics, local search, SAT solvers, simulation
 * efficient data structures (including e.g. dynamic, geometric, and spatial datastructures)
 * experimental algorithmics, applications
 * formal models of systems (including e.g. concurrent, hybrid, reactive, mobile, net-based, 
   and timed systems)
 * graph structure and algorithms,
 * intelligent algorithms,
 * logics of computation, process models, program synthesis
 * machine learning theory,
 * multi-agent algorithms and games,
 * nature-inspired computing,
 * network science,
 * neural network theory,
 * parallel and distributed computing,
 * quantum computing,
 * robotics
 * structural complexity,
 * visualization algorithms (including e.g. graph drawing, network layout)
and other relevant theory topics in computing and AI.
Program Chairs
Vera Kurkova, Czech Academy of Sciences, Prague, Czech Republic
Rastislav Kralovic, Comenius University, Bratislava, Slovakia
Program Committee
Amir Amihood, Bar-Ilan University, Israel
Přemysl Brada, University of West Bohemia, Czech Republic
Tiziana Calamoneri, Sapienza University of Rome, Italy
Ivana Cerna, Masaryk University, Brno, Czech Republic
Jérémie Chalopin, LIS Marseille, France
Marek Chrobak, University of California Riverside, USA
Gianluca De Marco, University of Salerno, Italy
Stefan Dobrev, Slovak Academy of Sciences, Slovakia
Martin Drozda, Slovak University of Technology in Bratislava, Slovakia
Robert Ganian, Technische Universität Wien, Austria
Leszek Gasieniec, University of Liverpool, UK
Cyril Gavoille, LaBRI, Université de Bordeaux, France
Lucjan Hanzlik, CISPA Helmholtz Center for Information Security, Germany
Markus Holzer, Universität Giessen, Germany
Ling-Ju Hung, National Taipei University of Business, Taiwan
Petr Jancar, Palacky University Olomouc, Czech Republic
Galina Jiraskova, Slovak Academy of Sciences, Slovakia
Tomasz Jurdzinski, University of Wroclaw, Poland
Petteri Kaski, Aalto University, Finland
Philipp Kindermann, Universität Trier, Germany
Dennis Komm, ETH Zurich, Switzerland
Daniel Krizanc, Wesleyan University, Middletown, USA
Giuseppe Liotta, University of Perugia, Italy
Alexei Lisitsa, University of Liverpool, UK
Hsiang-Hsuan Liu, Utrecht University, The Nederlands
Alessio Mansutti, IMDEA Software Institute, Spain
Marco Mesiti, University of Milano, Italy
Xavier Munoz Lopez, Universitat Politècnica de Catalunya, Spain
Vangelis Paschos, Université Paris-Dauphine, France
Rajeev Raman, University of Leicester, UK
Peter Rossmanith, RWTH Aachen, Germany
Pawel Sobocinski, Tallinn University of Technology, Estonia
Ulrike Stege, University of Victoria, Canada
Gerth Stølting Brodal, Aarhus University, Denmark
Submission Guidelines
Papers should be submitted electronically through EasyChair.
Submissions should be prepared in accordance with Springer’s Instructions for
Authors of Proceedings, and use either the LaTeX or the Word templates provided
on the authors’ page. The length should not exceed 12 pages (excluding
references).
No prior publication or simultaneous submission to other conferences or
journals are allowed (except preprint repositories such as arXiv or workshops
without formal published proceedings). There is no need to anonymize the
submissions.
Important Dates
Submission Deadline: September 15, 2024
Conference: January 20-23, 2025
Steering Committee
Henning Fernau, Trier University, Trier, Germany, chair
Leszek A. Gąsieniec, University of Liverpool, United Kingdom
Serge Gaspers, UNSW Sydney, Australia
Ralf Klasing, CNRS and University of Bordeaux, France
Tiziana Margaria, University of Limerick, Ireland
Mirosław Kutyłowski, NASK – National Research Institute, Warsaw, Poland
Branislav Rovan, Comenius University, Bratislava, Slovakia
Jan van Leeuwen, Utrecht University, Utrecht, The Netherlands
Július Štuller, Academy of Sciences, Prague, Czech Republic

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IROS 2024 Workshop: Standing the Test of Time Retrospective and Future of World Representations for Lifelong Robotics

July 23rd, 2024 Daniela Lopez de Luise
Dear community,
 
We are happy to welcome contributions to our IROS 2024 workshop: “Standing the Test of Time Retrospective and Future of World Representations for Lifelong Robotics”.
Accurate, informative, and scalable world representations are an essential component of highly autonomous mobile robots and have been an important topic of research for several decades. As robots become more capable, deploying in larger and more dynamic, varied environments, requirements for such representations have grown apace. Handling multiple data modalities, levels of abstraction, and types of information (metric, topological, semantic, objects, etc.) remains challenging — even more so in so-called lifelong settings where robots must maintain world models over extended periods of time. Over the last forty years, roboticists have used techniques from many machine learning and statistics paradigms for mapping. However, none have been nearly as transformative as deep learning, and we are now at an inflection point in the pace of adoption and proliferation of deep learning techniques for representing models of the world suited to robotics. Such a moment offers an opportunity for retrospection: to consider lessons from previous eras of research that have stood the test of time, to carry such lessons forward into an age of research dominated by models relying on latent representations, and to understand in hindsight the limits and blind spots of previous paradigms. We may look forward as well: to understand the trade-offs presented by newer learning and representation techniques, to share and discuss new examples of state-of-the-art technical approaches for robotic mapping and modelling, and to develop a shared view of the new frontier of challenges facing such systems as they are deployed in ever more challenging domains.
With these goals and challenges in mind, we extend a call for the following types of papers for submission to the Workshop:
Technical papers (up to 6 pages). Technical papers propose new methods for mapping or new world representations that represent the state-of-the-art in some aspect. Specific topics could include novel:
  • Time-aware predictive world models;
  • Action-conditioned world representations;
  • Methods for updating maps over many deployments or long time periods;
  • Hierarchical representations of environments;
  • Methods that explicitly support structure learning in the environment;
  • Methods for representing different information (e.g. spatiosemantic maps)” to “Methods for representing different types of information (e.g. spatial, temporal, semantic);
  • Methods for memory-efficient map storage;
  • Mapping primitives (e.g. Gaussian splatting, voxels, planes, etc.);
  • Mapping data structures (e.g. oct-trees, place graphs, etc.).
Retrospective papers (up to 8 pages). Retrospective papers are survey papers or other studies examining existing research at scale. They do not have to be exhaustive but should provide a solid foundation for a more comprehensive survey or tutorial article. Such papers may taxonomize previous mapping research, identify important lessons from previous eras of research that have stood the test of time, discuss how to carry such lessons forward into an age of research dominated by models relying on latent representations, or provide insight into the limits and blind spots of previous paradigms.
Mini retrospectives (up to 4 pages). Mini retrospectives are unique to this workshop and analyse how 1 or 2 related papers that are at least 5 years old have changed the way we think about world representations. Their focus is narrow, with an emphasis on detailed studies of a single theme.
Position papers (4-8 pages). Position papers look to the future and argue for the importance of certain techniques, questions, evaluation paradigms, design philosophies, etc. in future research. They may also elaborate on particular trade-offs presented by newer learning and representation techniques or develop a view of new difficulties facing state-of-the-art systems as they are deployed in ever more challenging domains.
This workshop is non-archival, and thus we are happy to review submissions that are concurrently under review elsewhere or have already been published in whole or in part.
Submission Instructions: Coming soon…
Important deadlines (subject to change)
  • Submission Deadline: Sunday, Sept 1, 2024, by 11:59 PM EDT
  • Reviews due: Friday, Sep 20, 2024, by 11:59 PM EDT
  • Acceptance Notification: Tuesday, Oct 1, 2024
  • Camera-ready submission: Tuesday, Oct 8, 2024, by 11:59 PM EDT
  • Workshop: Monday, October 14, 2024
  • Location: Room 17, more info to come!
 
Organisers:
Miguel Saavedra Ruiz, University of Montreal
Pierre-Yves Lajoie, University of Montreal
Samer Nashed, University of Montreal
Victor Romero Cano, Cardiff University
Liam Paull, University of Montreal
Malika Meghjani, Singapore University of Tech. & Design
John Leonard, MIT

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