<div dir="ltr">It is indeed an interesting one. <div><br></div><div><div>Thanks <br></div><div>Prakhar <br><div><br></div><div><br></div></div></div></div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Mon, Mar 11, 2024 at 3:41 PM Tim Oates <<a href="mailto:oates@cs.umbc.edu" target="_blank">oates@cs.umbc.edu</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex">An interesting competition.<br>
<br>
<br>
---------------------------------------<br>
Tim Oates, Professor<br>
Department of CS and EE<br>
University of Maryland Baltimore County<br>
(410) 455-3082<br>
<a href="https://coral-lab.umbc.edu/oates/" rel="noreferrer" target="_blank">https://coral-lab.umbc.edu/oates/</a><br>
<br>
---------- Forwarded message ----------<br>
Date: Thu, 7 Mar 2024 04:29:41 -0800 (PST)<br>
From: Abhinav Dhall <<a href="mailto:dhallabhinav@gmail.com" target="_blank">dhallabhinav@gmail.com</a>><br>
To: IKDD News <<a href="mailto:ikdd-news@googlegroups.com" target="_blank">ikdd-news@googlegroups.com</a>><br>
Subject: [IKDD News] 1Million Deepfakes Detection Challenge @ ACM Multimedia<br>
<br>
Call for Participation - 1 Million Deepfakes Detection<br>
Challengehttps://<a href="http://deepfakes1m.github.io/" rel="noreferrer" target="_blank">deepfakes1m.github.io/</a> <br>
at ACM Multimedia 2024, Melbourne<br>
<br>
The tremendous progress in generative AI has made the generation and<br>
manipulation of synthetic data easier and faster than before. To this end,<br>
multiple use cases are benefitting from it. The negative aspect of this<br>
progress and wide adoption of generative AI is deepfakes. Audio/image/video<br>
of an individual(s) is manipulated using generative methods without<br>
permission from the individual(s). This can make them be shown saying or<br>
doing something, which they may not have done in real. These unethically<br>
manipulated videos, popularly known as deepfakes have wide repercussions and<br>
negative effects on society in the form of the deepfakes? potential in<br>
spreading disinformation and misinformation. Deepfakes unfortunately are<br>
used for trolling online as well. Authentication systems such as video KYC<br>
(Know Your Customer) are also not resilient as often face recognition and<br>
verification systems are deceived when high-quality deepfakes are used. To<br>
this end, it is important for platforms and systems to be able to identify<br>
if manipulation has been performed on a media. These systems, which detect<br>
and analyse the deepfakes are referred to as deepfakes detectors.<br>
<br>
The 1M-Deepfakes Detection Challenge comprises of two sub-tasks:<br>
<br>
a. Deepfake Detection ? Given an audio-visual sample containing a single<br>
subject, the task is to identify if the video is a deepfake or real.<br>
<br>
b. Deepfakes Temporal Localisation ? Given an audio-visual sample containing a<br>
single subject, the task is to find out the frames (time stamps) in which<br>
the manipulation is done. The assumption here is that from the perspective<br>
of spreading misinformation, editing a few vital parts of a video may be<br>
enough to change the meaning of the original video, and at the same time,<br>
the quality of the deepfake video will be closer to the original compared to<br>
a deepfake in which the entire original video is manipulated.<br>
<br>
Challenge Registration - <a href="https://deepfakes1m.github.io/" rel="noreferrer" target="_blank">https://deepfakes1m.github.io/</a><br>
<br>
Timeline<br>
Training and Validation Data - available now<br>
Test Data - mid-May<br>
Paper submission deadline - June 14<br>
<br>
Thanks,<br>
Abhinav Dhall<br>
<br>
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</blockquote></div>