3rd Workshop on Image/Video/Audio Quality in Computer Vision and Generative AI

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Welcome to the 3rd Workshop on Image/Video/Audio Quality in Computer Vision and Generative AI!

Important Dates/Links:

Submission Deadline: 31 October, 2023 -> 03 November, 2023
Submission Link: https://cmt3.research.microsoft.com/WVAQ2024
Acceptance Notification Deadline: 10 November, 2023 -> 13 November, 2023
Camera Ready Papers Submission Deadline: 19 November, 2023 -> November 17, 2023, at 11:59 PM Pacific Daylight Time.
Workshop Day: 07 January, 2024
Workshop Website: https://wacv2024-workshop-quality-iva.github.io/workshop-quality-iva/index.html

Description:

Many machine learning tasks and computer vision algorithms are susceptible to image/video/audio quality artifacts. Nonetheless, most visual learning and vision systems assume high-quality image/video/audio as input. In reality, noises and distortions are common in image/video/audio capturing and acquisition process. Oftentimes, artifacts can be introduced in the video compression, transcoding, transmission, decoding, and/or rendering process. All of these quality issues play a critical role on the performance of learning algorithms, systems and applications, therefore could directly impact the customer experience.

Topics:

This workshop addresses topics related to image/video/audio quality in machine learning, computer vision, and generative AI. The topics include, but are not limited to:

Impact of image/video/audio quality in traditional machine learning and computer vision use cases such as object detection, segmentation, tracking, and recognition;
Analyze, model and learn the quality impact from image/video/audio acquisition, compression, transcoding, transmission, decoding, rendering, and/or display;
Techniques used to improve image/video/audio quality in terms of
- brightening, color adjustment, sharpening, inpainting, deblurring, denoising, de-hazing, de-raining, demosaicing,
- removing artifacts such as shadows, glare, and reflections, etc.,
- resolution, frame rate, color gamut, dynamic range (SDR vs. HDR), etc.,
- noise/echo cancellation, speech enhancement, etc.;
Novel image/video/audio quality assessment methodologies: full reference, reduced-reference, and non-reference;
Impact of image/video/audio quality in multi-modal use cases;
Evaluate image/video/audio quality produced by generative AI;
Techniques to detect and mitigate audio/video synchronization issue;
Techniques to measure the quality consistency across different types of content in video (such as ads, movies, streamed content, etc.);
Datasets, statistics, and theory of image/video/audio quality;
Research, applications and system development of the above.

Submission Guidelines and Review Process:

Authors are encouraged to submit high-quality, original (i.e., not been previously published or accepted for publication in substantially similar form in any peer-reviewed venue including journal, conference or workshop) research.
All submissions should follow the same template as for the main WACV2024 conference. Please refer to the WACV author kit .
The main paper has an 8-page limit, references do not count toward this. There is no limit on the number of pages in the supplementary material. Only pdf files are accepted.
Unlike the main conference(WACV2024), the review process for this workshop has only one round, and is single-blind. Authors do not have to be anonymized when submitting their work.
Please submit your paper via this link: https://cmt3.research.microsoft.com/WVAQ2024
Authors of accepted papers will be notified via email by: 10 November, 2023

Competition

Alongside the workshop we are hosting a Grand Challenge on the identification of audiovisual synchronization (AV-Sync) errors. An AV-Sync error, the temporal misalignment of audio relative to the video, is a defect that can have a large impact on a viewer’s Quality of Experience. The Telecommunications Union’s Rec. ITU-T J.248: Requirements for operational monitoring of video-to-audio delay in the distribution of television programs (2008) used subjective experiments to determine participants could detect an AV-Sync error if the audio leads the video by greater than 45 ms and if the audio lags the video by greater than 125 ms.

The Grand Challenge will consist of two tasks:

AV-Sync Error Detection - participants will make a binary prediction whether the audio is out-of-sync with the video. For more information please see: https://www.codabench.org/competitions/1541/
AV-Sync Error Measurement - participants will predict a quantitative measure of the magnitude of the AV-Sync Error. For more information please see: https://www.codabench.org/competitions/1543/

The two tasks will have a combined prize fund of $12000. We invite participants to enter one or both of the tasks at the links above with the following timelines:

2023-10-11 - Release of the Training Dataset
2023-10-11 - Initial Submission Opens
2023-12-02 00:00:00 UTC - Challenge Closes (Final Submissions: 1. to leaderboard and 2. summary report, model and weights)
2023-12-15 - Announcement of Awardees
2023-12-22 - Workshop Presentation Signup Deadline
2024-01-07 - WACV 2024 Workshop Day

Keynotes

Keynote Speaker: Ivan V. Bajić

Title: "Visual Coding for Humans and Machines"

Abstract: Visual content is increasingly being used for more than human viewing. For example, traffic video is automatically analyzed to count vehicles, detect traffic violations, estimate traffic intensity, and recognize license plates; images uploaded to social media are automatically analyzed to detect and recognize people, organize images into thematic collections, and so on; visual sensors on autonomous vehicles analyze captured signals to help the vehicle navigate, avoid obstacles, collisions, and optimize their movement. The above applications require continuous machine-based analysis of visual signals, with only occasional human viewing, which necessitates rethinking the traditional approaches for image and video compression. This talk is about coding visual information in ways that enable efficient usage by machine learning models, in addition to human viewing. We will touch upon recent rate-distortion results in this field, describe several designs for human-machine image and video coding, and briefly review related standardization efforts.

Bio: Ivan V. Bajić is a Professor of Engineering Science and co-director of the Multimedia Lab at Simon Fraser University, Canada. His research interests include signal processing and machine learning with applications to multimedia processing, compression, and collaborative intelligence. His group’s work has received several research awards, including the 2023 TCSVT Best Paper Award, conference paper awards at ICME 2012, ICIP 2019, MMSP 2022, and ISCAS 2023, and other recognitions (e.g., paper award finalist, top n%) at Asilomar, ICIP, ICME, ISBI, and CVPR. Ivan has served on the organizing and/or program committees of the main conferences in his field, and has received several awards in these roles, including Outstanding Reviewer Award (six times), Outstanding Area Chair Award, and Outstanding Service Award. He was on the editorial boards of the IEEE Transactions on Multimedia and IEEE Signal Processing Magazine, and is currently a Senior Area Editor of the IEEE Signal Processing Letters.

Keynote Speaker: Kevin Bowyer

Title: "Gray Face: Could Grayscale Be Better Than Color for Face Recognition?"

Abstract: Informally, color images may be perceived as higher quality than grayscale. All major face image datasets used by the research community contain RGB color images, and all deep CNN face matchers process color images. But, do CNN face matchers that work with color face images achieve better accuracy than equivalent matchers working with equivalent grayscale images? This talk examines this question in detail, and concludes that grayscale could in fact be better than color for deep CNN face matchers.

Bio: https://engineering.nd.edu/faculty/kevin-bowyer/

3rd Workshop on Image/Video/Audio Quality in Computer Vision and Generative AI

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Important Dates/Links:

Description:

Topics:

Submission Guidelines and Review Process:

Competition

Organizers

Yarong Feng

Yuan Ling

Joe Liu

Hai Wei

David Higham

Keynotes

Keynote Speaker: Ivan V. Bajić

Title: "Visual Coding for Humans and Machines"

Keynote Speaker: Kevin Bowyer

Title: "Gray Face: Could Grayscale Be Better Than Color for Face Recognition?"

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