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August 5th, 2021
Daniela Lopez de Luise
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August 5th, 2021
Daniela Lopez de Luise We invite workshop proposals for the 2022 IEEE Winter Conference of
Applications on Computer Vision (WACV 2022). WACV 2022 will be held as
an in-person conference with associated in-person workshops in Waikoloa,
Hawaii, January 4-8, 2022.
The workshop proposals should focus on topics related to computer vision
and its applications, interdisciplinary themes with other scientific and
application areas, as well as emerging challenges or competitions. The
format, style, and content of accepted workshops are under the control
of the workshop organizers and largely autonomous from the main
conference. Workshop organizers are expected to manage their technical
programs, invite experts in the domain, and maintain a website for the
workshop. Workshop registration and logistics will be handled by the
main conference.
*** Important Dates ***
Workshop proposal deadline: August 16th, 2021
Workshop acceptance notification: August 23rd, 2021
*** Submission Instructions ***
Proposals should clearly specify the following:
+ Workshop title, topic and tentative call for papers
+ Motivation, impact, and expected outcomes
+ Brief bios of organizers (including email and web pages)
+ Tentative program committee
+ Format (select either half or full day) and preliminary schedule
+ Tentative invited speakers
+ Estimated number of submissions and attendees
+ Plans (if any) for a special journal issue or book
Workshop proposals should be submitted in PDF via email to the Workshops
Co-Chairs (vitomir.struc@fe.uni-lj.si and betke@bu.edu). Proposals will
be evaluated by the workshop chairs and conference organizers, with an
eye towards selecting high-quality workshops on a diverse set of topics
that will inform and inspire the community.
*** Contact***
For questions and concerns, please contact
Margrit Betke (betke@bu.edu) and Vitomir Štruc (vitomir.struc@fe.uni-lj.si)
Workshops Co-Chairs WACV 2022
August 5th, 2021
Daniela Lopez de Luise Two powerful classes taught by expert imaging specialists Peter Burns and Don Williams + photography pro Uwe Artmann and Kevin Matherson, Microsoft Director of Optical Engineering.
SC01 – Imaging Quality for Automotive and Machine Vision Applications
Don Williams, Image Science Associates
Peter Burns, Burns Digital Imaging
13:00 – 15:30 London / 08:00 – 10:30 New York
The course covers current initiatives, progress, and challenges to specifying and evaluating imaging performance for automotive applications.
SC02 – Optics and Hardware Calibration of Compact Camera Modules for AR/VR, Automotive, and Machine Vision Applications
Uwe Artmann, Image Engineering GmbH & Co. KG
Kevin J. Matherson, Microsoft Corporation
16:00 – 18:30 London / 11:00 – 13:30 New York
The course provides an overview of issues associated with compact imaging modules used in mobile and digital imaging.
Short course registration includes access to recorded courses to view until February 2022.
Learn more about the courses: https://bit.ly/LIM_2021_ShortCourses
Elevate Your Experience—Combine the Technical Program + Short Courses for 15% savings off individual meeting and course registration
London Imaging Meeting 2021 (LIM 2021)
20-22 September Online
https://bit.ly/LIM_2021
Connect with us on Linkedin: https://www.linkedin.com/company/society-for-imaging-science-and-technology-is&t-/
Twitter: https://twitter.com/ImagingOrg #Londonimaging
Roberta Morehouse
Communications and Marketing Manager
Society for Imaging Science and Technology (IS&T)
—imaging across applications— http://www.imaging.org/
IS&T is a non-profit organization dedicated to advancing science and technology in the field of imaging.
August 5th, 2021
Daniela Lopez de Luise Apologies if you receive this more than once.
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About IWDSC
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Smart camera networks are becoming a fundamental piece of our intelligent cities, buildings, and homes, progressively inserting themselves into our lives. From smart surveillance systems composed of a multitude of smart camera nodes to small wearable cameras able to render a visual log of our daily experience, these devices interact with each other and with a wealth of other smart things, and of course the internet. Their rapid development is possible thanks to the convergence of several technologies. From advanced image sensors and vision chips to embedded vision systems capable of efficient feature extraction, image encoding and wireless transmission of the relevant visual content: This technology opens the door to new application domains, where video analytics and the extraction of semantic information from the scene is performed in a distributed fashion, implementing a new type of cooperative and/or collaborative vision.
The IWDSC team has previously organized 12 editions of the International Conference on Distributed Smart Cameras (ICDSC) with ACM as an international forum to discuss recent advances and open issues in these topics.
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Papers are invited in the following and related areas:
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=> Smart cameras in Internet of Things (IoT), Industry 4.0 and smart transport
– Smart cameras as IoT sensors
– Intelligent traffic cameras
– Smart IoT security camera for smart homes
– Smart cameras for Industry 4.0
– Vision sensors in Vehicular Ad- hoc Networks (VANETs)
=> Mobile Vision, 3D and Robotics
– 3D reconstruction of everything
– Driver assistance, autonomous driving
– Social robot
– Drone distributed smart cameras
– Structure-from-motion in mobile devices
– Visual landmark localization
– Active vision and mobile/body-worn cameras
– Position discovery and middleware apps
=> Smart image sensors and vision chips
– Circuits and systems for image sensing
– Parallel processing hardware
– Camera beyond the visual spectrum
– HW/S W codesign for embedded vision
– Reconfigurable vision processing architectures
– High-performance image sensors
– Neuromorphic cameras and networks
=> Machine learning in distributed camera networks
– Deep learning on smart cameras
– Transforming embedded vision through deep learning
– Distributed learning algorithms in visual sensor networks
– Novel machine learning technology implementation on smart cameras
– Machine learning for low-powered sensors
– Artificial intelligence and deep learning at the edge
=> Distributed smart cameras and network architectures
– Camera system designs and architectures
– Architectures for camera networks
– Embedded vision programming
– Distributed video coding
– Self-reconfiguring camera networks
– Self-organizing smart cameras
– Wireless and mobile image sensor network s
– Context-aware networks
– Distributed video analytics
– Resource management and task allocation
– Data aggregation and information fusion
– Collaborative object recognition and extraction
=> Emerging applications
– Process splitting in-camera vs cloud
– Virtual reality and augmented reality
– Smart cameras and semantic information
– Smart cities and smart cameras
– Camera-based health and wellness monitoring
– AI and video analytics for smart cameras
– Social media and big data
– Smart cameras for situational intelligence and interaction
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Submission
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The submission site is open, and accessible at: https://cmt3.research.microsoft.com/DSC2021
Each paper will be reviewed by at least two members of the Scientific Program Committee, in a double-blind fashion. The submitted papers should present original work, not currently under review elsewhere, and should have no substantial overlap with already published work. Submissions should be submitted in PDF and should be no more than 8 pages following the ICCV main Conference paper format and guidelines (https://iwdsc.github.io/submissions/).
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Important Dates
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Paper Submission Deadline: August 4, 2021 (11:59PM Pacific Time)
Reviews Released to Authors: August 11, 2021 (11:59PM Pacific Time)
Camera ready due: August 16, 2021 (11:59PM Pacific Time)
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Proceedings and Special Issue
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Accepted papers will be published within the ICCV Workshop Proceedings. Authors of high quality papers will be invited to extend their work and submit it for a special issue in a JCR-indexed journal.
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Oranizing Team
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Niki Martinel, University of Udine, Italy
Ehsan Adeli, Stanford University, USA
Caifeng Shan, Shandong University of Science and Technology, China
Anima Anandkuma, Caltech/NVidia, USA
Yue Gao, Tsinghua University, China
Hamid Aghajan, Gent University, Belgium
Christian Micheloni, University of Udine, Italy
Fei-Fei Li, Stanford University, USA
August 5th, 2021
Daniela Lopez de Luise
FYI, machine learning is one of the highlighted topics
Apologize for multiple postings!