The exact date of the workshop will be announced.
Every day over 450 million photos and videos are being uploaded to Facebook and Instagram. The
exponential growth of visual media has made quality assessment become increasingly important for
various applications, including image and video acquisition, synthesis, restoration, enhancement,
search and retrieval, storage, and recognition.
Broadly, visual quality assessment techniques can be divided into image and video technical
quality assessment (IQA and VQA, or broadly TQA) and aesthetics quality assessment (AQA). TQA
focuses on the effect of image-level technical aspects of perceived quality, such as sharpness,
noise, color reproduction, contrast, dynamic range, and others. On the other hand, AQA deals with
more abstract aesthetics-related quality factors that capture the subjective aesthetics experience.
Aesthetics judgments are associated with the adherence to established photographic rules
encompassing lighting (emphasis, contrast), composition, colors, and more. Even though these topics
have mostly been studied independently, they represent tightly related aspects of the same
underlying subjective experience of media items, value judgments.
This workshop aims to bring together individuals in the two fields of TQA and AQA for sharing of
ideas and discussions on current trends, developments, issues, and future directions, with the
vision to accelerate the progress of research in both fields. Our hope is that bridging TQA and
AQA, will result in a better understanding of quantitative measures of quality of experience in the
broader context of multimedia applications.
The scope of this workshop spans:
- Analysis and prediction of aesthetic and technical visual quality, encompassing absolute and
comparative judgments about visual media:
- Traditional and deep-learning-based approaches
- Aesthetics and QoE related concepts such as interestingness, popularity, viralness
- Datasets for TQA and AQA, including:
- New approaches to data collection procedures and sources
- New data augmentation methods
- Applications of TQA and AQA in computer vision or image processing tasks:
- Visual filtering and retrieval (recommendation, image gallery/video)
- Visual editing (recomposition, retargeting, cropping)
- Assessment guided visual enhancement
- Real-world systems and applications
- Applications to media such as light fields, 360 or stereo, point clouds.
29th June 2020: Submission Deadline for Workshop
2nd August 2020: Notification of Acceptance of Workshop Papers
16th August 2020: Workshop Camera-Ready Papers Due
All deadlines are at midnight (23:59) Anywhere on Earth.
As of 28th March 2020, there are no changes for the workshop paper submission deadlines. Unless
we hear anything different from the Conference organizers, the dates are as advertised
Authors are invited to submit a full paper (two-column format, 6-8 pages, not including
references) electronically according to the guidelines available on the conference website at
2020.acmmm.org. We use the same formatting template as ACM
Multimedia 2019. All contributions must be submitted through CMT using the following link:
Please find the
call for papers here.
Speaker: Alan Conrad Bovik
Alan Conrad Bovik is an American engineer and vision scientist. He is a Professor at The
University of Texas at Austin (UT-Austin), where he holds the Cockrell Family Regents Endowed Chair
and is Director of the Laboratory for Image and Video Engineering. He is a faculty member in the
UT-Austin Department of Electrical and Computer Engineering, the Institute for Neuroscience, and
the Wireless Networking and Communications Group. Bovik won a Primetime Emmy Award in 2015 for his
development of video quality measurement tools that are now standards in television production. Two
of Bovik’s research publications in the area of visual image quality have been recognized as 2017
Google Scholar Classic Papers, which are selected for being highly-cited papers that have stood the
test of time, and are among the ten most-cited articles in their area of research published ten
Talk title and abstract: TBA.
Speaker: James Z. Wang
James Z. Wang is a professor at Pennsylvania State University. Wang’s research seeks to advance
knowledge through modeling objects, concepts, aesthetics, and emotions in big visual data. He is
well-known for his pioneering research in the field of aesthetics quality assessment. His research
team have developed the ACQUINE aesthetic quality inference engine, SIMPLIcity semantics-sensitive
image retrieval system, the ALIPR real-time computerized image tagging system, which are all widely
cited. His research has been reported widely by significant media, including Discovery, Scientific
American, MIT Tech Review, Public Radio, NPR, and CBS. Wang also received an NSF Career award and
the endowed PNC Technologies Career Development Professorship.
Talk title and abstract: TBA.
To be announced.
Wen-Huang Cheng, NCTU, Taiwan
Goldlücke, Uni-KN, Germany, SFB-TRR 161
Uni-KN, Germany, SFB-TRR 161
Weisi Lin, NTU, Singapore
Saupe, Uni-KN, Germany, SFB-TRR 161
John See, MMU, Malaysia
Lai-Kuan Wong, MMU, Malaysia
John See, and
Lai Kuan Wong.