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From:
Cise Midoglu <[log in to unmask]>
Reply To:
Cise Midoglu <[log in to unmask]>
Date:
Mon, 12 Apr 2021 07:30:15 +0200
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Dear colleagues,

There are multiple grand challenges hosted by the ACM Multimedia Systems
(MMSys) Conference 2021, which will take place in Istanbul between
September 28 - October 1.

Register by: June 25th

Upload by: June 28th

Notifications on: July 23rd

Camera-ready due: August 6th

Awards: For each challenge, the winner will be awarded $5,000 and the
runner-up will be awarded $2,500.

Winners will be chosen by a committee appointed by the challenge organizers
and results will be final. All accepted submissions will be published as
part of the MMSys’21 proceedings in the ACM Digital Library. Also note that
MMSys’21 will offer a large number of travel grants to students as well as
attendees from minority groups and less fortunate countries. All details
regarding the calls, submission formats and travel grants are available at
https://2021.acmmmsys.org.


Grand Challenge on Bandwidth Estimation for Real-Time Communications

https://2021.acmmmsys.org/rtc_challenge.php

Sponsored by: Microsoft and OpenNetLab

A pivotal algorithm to optimize the QoE for real-time video communications
is bandwidth estimation. It runs on the endpoint of a real-time video
application and aims at adapting the video bitrate dynamically to stay
within the available network capacity. To this end, it generally collects
packet statistics from the network path and regularly computes a bandwidth
estimate for the future. It then passes the estimate into a video codec as
a target bitrate, requesting the codec to encode video frames in an average
bitrate approximately equivalent to the target. As a result, the bandwidth
estimator avoids network oversubscription by controlling the sending rate
of video indirectly through the codec. In this challenge, we call for a
novel bandwidth estimation scheme implemented in the provided framework,
such that it is able to attain superior overall QoE on a real-world testbed
we built for real-time communications (RTC) of video and audio.


Grand Challenge on Detecting Cheapfakes

https://2021.acmmmsys.org/cheapfake_challenge.php

Sponsored by: YouTube, Simula Metropolitan Center for Digital Engineering
(SimulaMet), University of Bergen (UiB), Technical University of Munich
(TUM)

Cheapfake is a general term that encompases many non-AI "cheap"
manipulations of multimedia content, including the use of editing software
such as Photoshop, but also the alteration of context, etc. Cheapfakes are
in fact known to be more prevalent than deepfakes. In this challenge, we
aim to benchmark algorithms that can be used to detect out-of-context
(image, caption1, caption2) pairs in news items based on a recently
compiled dataset. Note that we do not consider digitally altered, or "fake"
images, but rather focus on detecting the misuse of real photographs with
conflicting image captions. Our current scope is limited to the English
language, as the test dataset does not include captions from other
languages.


Follow Us

https://twitter.com/acmmmsys/

https://www.linkedin.com/groups/12430121/

https://tinyurl.com/mmsys-wechat
Join our Slack workspace: https://tinyurl.com/mmsys-slack
<https://tinyurl.com/mmsys-slack>

-- 
Cise Midoglu
Simula Research Laboratory
https://www.simula.no

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