[image 04621] [CFP] IEEE Multimedia Information Procesing & Retrieval (MIPR) 2022

[Ichiro IDE]

Image MLの皆様,

井手＠名大です．

お世話になっております．

以前にもご案内しましたが，IEEE MIPR 2022という国際会議のCFPをお送りし
ます．締切が3/28まで延長されましたので，今からでも是非投稿をご検討くだ
さい．

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The Fifth (2022) IEEE International Conference on
Multimedia Information Processing and Retrieval (MIPR'22)

http://www.ieee-mipr.org 
Taking Place Virtually
August 2 - August 4, 2022
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MIPR 2022 highlights

Keynote Speakers
* Philip S. Yu, Professor, University of Illinois Chicago 
* Jian Pei, Professor, Simon Fraser University  
* Shih-Fu Chang, Professor, Columbia University  

Innovation Forums
* The Future Trending of Metaverse
  Moderator: Shuxue Quan, Oppo
* Hardware and Software Acceleration for AI Applications
  Moderator: Xin Chen, Intel
* The Future of Media Compression: Deep Learning Approaches
  Moderator: Dong Liu, University of Science and Technology of China
* Computer Vision
  Moderator: Zhou Ren, Wormpex AI Research

New forms of multimedia data (such as text, numbers, tags, networking,
signals, geo-tagged information, graphs/relationships, 3D/VR/AR and
sensor data, etc.)  has emerged in many applications in addition to
traditional multimedia data (image, video, audio). Multimedia has
become the biggest of big data as the foundation of today's
data-driven discoveries. Almost all disciplines of science and
engineering, as well as social sciences, involve multimedia data in
some forms, such as recording experiments, driverless cars, unmanned
aerial vehicles, smart communities, biomedical instruments, security
surveillance.  Some recent events demonstrate the power of real-time
broadcast of unfolding events on social networks. Multimedia data is
not just big in volume, but also multi-modal and mostly
unstructured. Storing, indexing, searching, integrating, and
recognizing from the vast amounts of data create unprecedented
challenges. Even though significant progress has been made processing
multimedia data, today's solutions are inadequate in handling data
from millions of sources simultaneously. 

The IEEE International Conference on Multimedia Information Processing
and Retrieval (IEEE-MIPR) aims to provide a forum for original
research contributions and practical system design, implementation,
and applications of multimedia information processing and retrieval
for single modality or multiple modalities. The target audiences will
be university researchers, scientists, industry practitioners,
software engineers, and graduate students who need to become
acquainted with technologies for big data analytics, machine
intelligence, information fusion in multimedia information processing
and retrieval.  A collection of keynotes, tutorials, and workshops
will be held, together with paper/poster sessions.  In addition, MIPR
2022 Innovation Forum invites leaders in multimedia society to discuss
the topics covering video compression, AI acceleration, metaverse, and
Computer Vision.

The conference will accept regular papers (6 pages), short papers (4
pages), and demo papers (4 pages). Authors are encouraged to compare
their approaches, qualitatively or quantitatively, with existing work
and explain the strength and weakness of the new approaches. Selected
submissions will be invited to submit to journal special issues.

The conference includes (but not limited) the following topics of
multimedia data processing and retrieval.

Multimedia Retrieval
	Multimedia Search and Recommendation
	Web-Scale Retrieval
	Relevance Feedback, Active/Transfer Learning
	3D and sensor data retrieval
	Multimodal Media (images, videos, texts, graph/relationship)
	Retrieval
	High-Level Semantic Multimedia Features
	Machine Learning/Deep Learning/Data Mining
	Deep Learning in Multimedia Data and / or Multimodal Fusion
	Deep Cross-Learning for Novel Features and Feature Selection
	High-Performance Deep Learning (Theories and Infrastructures)
	Spatio-Temporal Data Mining
	Novel Dataset for Learning and Multimedia
	Content Understanding and Analytics
	Multimodal/Multisensor Integration and Analysis
	Effective and Scalable Solution for Big Data Integration
	Affective and Perceptual Multimedia
	Multimedia/Multimodal Interaction Interfaces with humans
	Multimedia and Vision
	Multimedia Telepresence and Virtual/Augmented/Mixed Reality
	Visual Concept Detection
	Object Detection and Tracking
	3D Modeling, Reconstruction, and Interactive Applications
	Networks for Multimedia Systems
	Internet Scale System Design
	Information Coding for Content Delivery
	Systems and Infrastructures
	Multimedia Systems and Middleware
	Software Infrastructure for Data Analytics
	Distributed Multimedia Systems and Cloud Computing
	Data Management
	Multimedia Data Collections, Modeling, Indexing, or Storage
	Data Integrity, Security, Protection, Privacy
	Standards and Policies for Data Management
	Novel Applications
	Multimedia applications for health and sports
	Multimedia applications for culture and education
	Multimedia applications for fashion and living
	Multimedia applications for security and safety
	Internet of Multimedia Things
	Real-Time Data Processing
	Autonomous Systems such as Driverless Cars, Robots, and Drones
	Mobile and Wearable Multimedia

* IEEE Technical Committee on Multimedia Computing (TCMC) will sponsor
  5-6 student registration scholarships. Preference will be given to
  student authors

Important Dates:
	Regular and Short Paper Submission: March 28, 2022 [Extended]
	Notification of acceptance: May 10, 2022
	Camera ready due: July 1, 2022  
	Conference Date: August 2 - 4, 2022 

General Co-Chairs:
	C.-C. Jay Kuo (University of Southern California, USA)
	Klara Nahrstedt (University of Illinois at Urbana-Champaign, USA)
	Yong Rui (Lenovo Group, China)
	Guan-Ming Su (Dolby Labs, USA)

Program Co-Chairs:
	Ming-Ching Chang (State University of New York at Albany, USA)
	Abdulmotaleb El Saddik (University of Ottawa, Canada)
	Yan Tong (University of South Carolina, USA)
	Bihan Wen (Nanyang Technological University, Singapore)
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--
■ 井手 一郎 					    ide ＠ i.nagoya-u.ac.jp  ■
■ 名古屋大学 大学院情報学研究科 知能システム学専攻			  ■
■ 	      ／数理・データ科学教育研究センター 基盤教育部門		  ■
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