ICIP 2023 Special Session on Autonomous Vehicle Vision (AVVision)

January 12th, 2023 Daniela Lopez de Luise

Early abstract submissions are required! Send your abstract (including tentative title, abstract, author list, and corresponding author affiliation and email) to Rui Fan (rui.fan@ieee.org) before January 29, 2023! If your abstract is within the scope of our special session, we will invite you to submit a full paper (4 pages). Please note: the paper review process for Special Session papers will be handled by the TPCs, along with the Regular Paper. The important dates and paper instructions are the same as Regular Paper.

 

Call for Papers 

Due to the recent boom in artificial intelligence technologies, there are growing expectations that fully autonomous driving may become a reality in the near future and it is expected to bring fundamental changes to our society. Fully autonomous vehicles offer great potential to improve efficiency on roads, reduce traffic accidents, increase productivity, and minimize our environmental impact in the process.

As a key component of autonomous driving, autonomous vehicle vision (AVVision) systems are typically developed based on cutting-edge computer vision, machine/deep learning, image/signal processing, and advanced sensing technologies. With recent advances in deep learning, AVVision systems have achieved compelling results. However, there still exist many challenges. For instance, the perception modules cannot perform well in poor weather and/or illumination conditions or in complex urban environments. Developing robust and all-weather visual environment perception algorithms is a popular research area that requires more attention. In addition, most perception methods are computationally-intensive and cannot run in real-time on embedded and resource-limited hardware. Therefore, fully exploiting the parallel-computing architecture, such as embedded GPUs, for real-time perception, prediction, and planning is also a hot subject that is being researched in the autonomous driving field. Furthermore, existing supervised learning approaches have achieved compelling results, but their performance is fully dependent on the quality and amount of labeled training data. Labeling such data is a time-consuming and labor-intensive process. Un/self-supervised learning approaches and domain adaptation techniques are, therefore, becoming increasingly crucial for real-world autonomous driving applications.

Research papers are solicited in, but not limited to, the following topics:

• 3D geometry reconstruction for autonomous driving;

• Driving scene understanding;

• Self-supervised/unsupervised visual environment perception;

• Driver status monitoring and human-car interfaces;

• Deep/machine learning and image analysis for autonomous vehicle perception;

• Adversarial domain adaptation for autonomous driving.

Organizers 

Dr. Rui Ranger Fan, Tongji University

Dr. Wenshuo Wang, McGill University

Important Dates

Paper Submission Deadline: February 15, 2023

Paper Acceptance Notification: June 21, 2023

Final Paper Submission Deadline: July 5. 2023

Submission

Paper Submission Instruction: https://cmsworkshops.com/ICIP2023/papers.php. The review process for Special Session papers will be handled by the TPCs, along with the Regular Paper. The important dates and paper instructions are the same as Regular Paper:

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CIAP 2023 – 22th International Conference on Image Analysis and Processing

January 12th, 2023 Daniela Lopez de Luise

Call for Papers

ICIAP 2023 is the 22th edition of a series of conferences organized biennially by CVPL, the Italian Member Society of the International Association for Pattern Recognition (IAPR).

The focus of the conference is on both classic and recent trends in computer vision, pattern recognition and image processing, and covers both theoretical and applicative aspects, with particular emphasis on the following topics:

● Pattern Recognition  
● Machine Learning and Deep Learning 
● 3D Computer Vision and Geometry 
● Image Analysis: Detection and Recognition 
● Video Analysis & Understanding
● Biomedical and Assistive Technology 
● Digital Forensics and Biometrics
● Multimedia 
● Cultural Heritage 
● Robot Vision and Automotive
● Shape representation  recognition and analysis: 
● Augmented and Virtual Reality
● Geospatial Analysis
● Computer Vision for UAVs

The conference will be held in Udine, Italy on 11-15th September, 2023.
The conference is structured in oral and poster sessions and offers invited lectures from distinguished speakers. Satellite workshops and tutorials are also organised.


Dates

● Paper Submission 1st round: 15  February  2023
● Notifications to Authors 1st round:  15  April 2023
● Paper Submission 2nd round:  1  May 2023 
● Notifications to Authors 2nd round: 1  July 2023
● Camera Ready papers due:  15  July 2023
● Main Conference:  12-14 September 2023
● Workshop and Tutorials:  11 and 15 September 2023

Submission


All submissions will be handled electronically via the conference’s CMT Website: 
https://cmt3.research.microsoft.com/ICIAP2023
Papers will be selected through a double-blind review process, taking into account originality, significance, clarity, soundness, relevance and technical contents. 
Each submission will be managed by two Area Chairs and reviewed by at least three reviewers. 
Accepted papers will be published in indexed conference proceedings.


People

General Chairs: Gian Luca Foresti (U. Udine)  Andrea Fusiello (U. Udine) , Edwin Hancock (U. York)
Program Chairs: Michael Bronstein (U. Oxford),  Barbara Caputo (Politecnico Torino),  Giuseppe Serra (U. Udine) 
Workshop Chairs: Federica Arrigoni (Politecnico Milano),  Lauro Snidaro (U. Udine) 
Tutorial Chairs: Christian Micheloni (U. Udine) , Francesca Odone (U. Genova)
Publication Chairs: Claudio Piciarelli (U. Udine) , Niki Martinel (U. Udine) 
Industrial Liaison Chairs:  Pasqualina Fragneto (STM)
Publicity/Social Chair:  Matteo Dunnhofer (U. Udine), Beatrice Portelli (U. Udine)
Local Organization Chairs:  Eleonora Maset (U. Udine), Andrea Toma (U. Udine), Emanuela Colombi (U. Udine), Alex Falcon (U. Udine)

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EarthVision Workshop @ CVPR 2023

January 12th, 2023 Daniela Lopez de Luise

 

CALL FOR PARTICIPANTS & PAPERS

 

EarthVision 2023 – Large Scale Computer Vision for Remote Sensing Imagery Workshop 

in conjunction with CVPR 2023, June 2023, Vancouver, Canada. 

 

Website: https://www.grss-ieee.org/earthvision2023/

 

AIMS AND SCOPE

Earth Observation (EO) and remote sensing are fast growing fields of investigation where computer vision, machine learning, and signal/image processing meet. The general objective of EO is to provide large-scale and consistent information about processes occurring at the surface of the Earth by exploiting data collected by airborne and spaceborne sensors. EO covers a broad range of tasks, from detection to registration, data mining, and multi-sensor, multi-resolution, multi-temporal, multi-modal fusion and regression, to name just a few. It serves numerous  applications such as location-based services, online mapping, large-scale surveillance, 3D urban modeling, navigation systems, natural hazard forecast and response, climate change monitoring, virtual habitat modeling, food security, etc. The sheer amount of data calls for highly automated scene interpretation workflows. 


The Earthvision workshop, held for its seventh edition at the CVPR 2023, aims at fostering collaboration between the computer vision, machine learning, and the remote sensing communities to boost automated analysis of EO data. EarthVision will strive to build cooperation within the CVPR community for this highly challenging and quickly evolving field with a significant impact on society, economy, industry, and the environment. 

 

We invite contributions in the fields of (not exhaustive list):

  • Super-resolution in the spectral and spatial domain

  • Hyperspectral and multispectral image processing

  • Reconstruction and segmentation of optical and LiDAR 3D point clouds

  • Feature extraction and learning from spatio-temporal data 

  • Analysis  of UAV / aerial and satellite images and videos

  • Deep learning tailored for large-scale Earth Observation

  • Domain adaptation, concept drift, and the detection of out-of-distribution data

  • Evaluating models using unlabeled data

  • Self-, weakly, and unsupervised approaches for learning with spatial data

  • Human-in-the-loop and active learning

  • Multi-resolution, multi-temporal, multi-sensor, multi-modal processing

  • Fusion of machine learning and physical models

  • Explainable and interpretable machine learning in Earth Observation applications

  • Applications for climate change, sustainable development goals, and geoscience

  • Public benchmark datasets: training data standards, testing & evaluation metrics, as well as open source research and development.

 

IMPORTANT DATES

Full paper submission: March 9, 2023

Notification of acceptance: March 30, 2023

Camera-ready paper: April 6, 2023

Workshop (full day): June 18, 2023

 

SUBMISSION GUIDELINES

A complete paper should be submitted using the EarthVision templates provided on the workshop website. The paper length must not exceed 8 pages (excluding references) and formatting follows CVPR 2023 instructions. All manuscripts will be subject to a double-blind review process, i.e. authors must not identify themselves on the submitted papers. The reviewing process is single-stage, meaning that there will not be rebuttals to reviewers.

 

Papers are to be submitted using the dedicated submission platform on the workshop website. By submitting a manuscript, the authors guarantee that it has not been previously published or accepted for publication in substantially similar form. CVPR rules regarding plagiarism, double submission, etc. apply.  

 

WORKSHOP ORGANIZERS

Ronny Hänsch, German Aerospace Center, Germany

Devis Tuia, EPFL, Switzerland

Jan Dirk Wegner, University of Zurich & ETH Zurich, Switzerland

Bertrand Le Saux, ESA/ESRIN, Italy

Nathan Jacobs, Washington University in St. Louis, USA

Loïc Landrieu, IGN, France

Charlotte Pelletier, UBS Vannes, France

Hannah Kerner, Arizona State University, USA

Beth Tellman, University of Arizona, USA

 

CHALLENGE

EarthVision 2023 will feature the African Biomass Challenge with the goal to accurately estimate aboveground biomass in different cocoa plantations in Côte d'Ivoire. The dataset consists of ESA Sentinel-2 images, NASA GEDI data and ground truth biomass. All AI practitioners, experts and enthusiasts are invited to take part in the competition organized on Zindi.

 

SPONSORING

The event is co-organized by the Image Analysis and Data Fusion Technical Committee of the IEEE-GRSS, and it is sponsored by Blacksky, Exolabs, Picterra, and Kitware.

 

Website: https://www.grss-ieee.org/earthvision2023/

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Neuro-symbolic AI for Agent and Multi-Agent systems [NeSyMAS] Workshop

January 12th, 2023 Daniela Lopez de Luise
We are excited to be sending out the call for the Neuro-symbolic AI for Agent and Multi-Agent systems workshop at AAMAS-2023. Details below. It is organized by the Turing special interest group (link at the bottom). Perhaps one of these of interest.

CALL FOR PAPERS: Neuro-symbolic AI for Agent and Multi-Agent systems [NeSyMAS] Workshop

[part of AAMAS 2023; London, UK; 29th May-2nd June 2023]

Paper submission link: https://easychair.org/my/conference?conf=nesymas2023

AI has vast potential, some of which has been realised by developments in deep learning methods. However, it has become clear that these approaches have reached an impasse and that such “sub-symbolic” or “neuro-inspired” techniques only work well for certain classes of problem and are generally opaque to both analysis and understanding. “Symbolic” AI techniques, based on rules, logic and reasoning, while not as efficient as “sub-symbolic” approaches, have better behaviour in terms of transparency, explainability, verifiability and, indeed, trustworthiness. A new direction described as “neuro-symbolic” AI combines the efficiency of “sub-symbolic” AI with he transparency of “symbolic” AI. This combination potentially provides a new wave of AI systems that are both interpretable and elaboration tolerant and can integrate reasoning and learning in avery general way.

Though there is work on neuro-symbolic AI for competing with classical ML models, such as its use of label-free supervision and graph embeddings, there is much less on the use for agent modelling or multi-agent systems. Especially in a multi-agent context, the use of symbolic models for mental state reasoning together with low-level perception patterns or formation of reasoning-capable representations from subsymbolic data, all represent promising areas where MAS offers a unique perspective.

This workshop's aim is thus to assemble leading-edge work in which neuro-symbolic AI approaches and MAS interact.

TOPICS. Topics of interest include, but are not limited to, the following: Explicit agency in neuro-symbolic multi-agent systems Neuro-symbolic Reinforcement Learning Neuro-symbolic robotics and planning Mental models and epistemic logics for MAS Multiagency flavours Symbolic knowledge representations for subsymbolic MAS Neural-symbolic multi-agent systems Hybrid agent architectures Formal analysis of neural-symbolic multi-agent systems

SUBMISSION. We welcome unpublished technical papers of up to 8 pages, and short (2-4 pages) position papers. Papers should be written in English, be prepared for single-blind reviewing, be submitted as a PDF document, and conform to the formatting guidelines of AAMAS 2023

Papers selected for presentation at the workshop will be included in the workshop's proceedings as open access publications, tentatively in CEUR.

DEADLINES. Important dates [All dates are 23:59 AoE] Paper submission deadline: 13 March 2023 Paper acceptance notification: 17 April 2023 Camera-ready deadline: 15 May 2023 Workshop: 29 or 30 May, 2023

Organising Committee Vaishak Belle, University of Edinburgh, UK Michael Fisher, University of Manchester, UK Xiaowei Huang, University of Liverpool, UK Masoumeh Mansouri, University of Birmingham, UK Albert Meroño-Peñuela, King's College London, UK Sriraam Natarajan, UT Dallas, USA Efi Tsamoura, Samsung Cambridge, UK

This workshop is organised by the Interest Group in Neuro-Symbolic AI of The Alan Turing Institute.
The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336. Is e buidheann carthannais a th' ann an Oilthigh Dhùn Èideann, clàraichte an Alba, àireamh clàraidh SC005336.

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ML4CPS in Hamburg – Deadline Extension

January 12th, 2023 Daniela Lopez de Luise

Please note that the Deadline for submission of full papers for ML4CPS – Machine Learning for Cyber-Physical Systems – 2023 in Hamburg has been extended to the 20th of January. Furthermore, we now also accept short papers. The Deadline for short papers will be the 27th of January.

 

We aim to bring together researchers and practitioners in the field of machine learning for technical systems.

 

All information can also be found on the website: ML4CPS – Machine Learning For Cyber-Physical Systems – Professur für Informatik im Maschinenbau (hsu-hh.de)

 

If you are using machine learning to analyze technical systems – be it robots, production lines, water systems or cars – this conference is for you!

 

We hope to see you in Hamburg next year!

 

Kind regards Maria Krantz

 

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