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</o:shapelayout></xml><![endif]--></head><body lang=EL link=blue vlink=purple style='word-wrap:break-word'><div class=WordSection1><div><div><div><div><div><div><p class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto'><span lang=EN-GB>********<o:p></o:p></span></p><p class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto'><span lang=EN-GB>Subject: AI4Media: CBMI 2023 Special Session on Computational Memorability of Imagery<o:p></o:p></span></p><p class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto'><span lang=EN-GB><br>Dear +++++++<o:p></o:p></span></p><div><p><span lang=EN-GB>Please find below the Call for Papers for the <a href="https://cbmi2023.org/special-sessions/#CMI" target="_blank">Special Session on Computational Memorability of Imagery</a> at CBMI 2023. The conference and special session are supported by the AI4Media project. <o:p></o:p></span></p><p><span lang=EN-GB>Please consider submitting your work to this special session. <o:p></o:p></span></p><p><span lang=EN-GB>Thank you,<o:p></o:p></span></p><p><b><span lang=EN-GB>------------------------------------------------------------------------------------------------</span></b><span lang=EN-GB><o:p></o:p></span></p><p><b><span lang=EN-GB>Computational Memorability of Imagery<br>Special Session at CBMI 2023</span></b><span lang=EN-GB><br>20-22 September 2023<br>Orleans, France<br><a href="https://cbmi2023.org" target="_blank">https://cbmi2023.org</a><br><br>The subject of memorability has seen an influx in interest since the likelihood of images being recognised upon subsequent viewing was found to be consistent across individuals. Driven primarily by the MediaEval Media Memorability tasks which has just completed its 5th annual iteration, recent research has extended beyond static images, pivoting to the more dynamic and multi-modal medium of video memorability.<br><br>The memorability of a video or an image is an abstract concept and like other features such as aesthetics and beauty, is an intrinsic feature of imagery. There are many applications for predicting image and video memorability including marketing where some part of a video advertisement should strive to be the most memorable, in education where key parts of educational content should be memorable, in other areas of content creation such as video summaries of longer events like movies or wedding photography, and in cinematography where a director may want to make some parts of a movie or TV program more, or less, memorable than the rest.<o:p></o:p></span></p><p><span lang=EN-GB>For computing video memorability, researchers have used a variety of approaches including video vision transformers as well as more conventional machine learning, text features from text captions, a range of ensemble approaches, and even generating surrogate videos using stable diffusion methods. The performance of these approaches tells us that we are now close to the best performance for memorability prediction for video and for images that we could get using current techniques and that there are many research groups who can achieve such a level of performance.<o:p></o:p></span></p><p><span lang=EN-GB>We believe that image and video memorability is now ready for the spotlight and for researchers to be drawn to using video memorability prediction in creative ways. We invite submissions from researchers who wish to extend their reported techniques and/or apply those techniques to real-world applications like marketing, education, or other areas of content production. We hope that the output from this special session will be a community-wide realization of the potential for video memorability prediction and uptake in research into, and applications of, the topic.<o:p></o:p></span></p><p><span lang=EN-GB>The topics of the special session include, but are not limited to:<o:p></o:p></span></p><ul type=disc><li class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l2 level1 lfo3'><span lang=EN-GB>Development and interpretation of single- or multi-modal models for Computational Memorability<o:p></o:p></span></li><li class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l2 level1 lfo3'><span lang=EN-GB>Transfer learning and transferability for Computational Memorability<o:p></o:p></span></li><li class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l2 level1 lfo3'><span lang=EN-GB>Computational Memorability applications<o:p></o:p></span></li><li class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l2 level1 lfo3'><span lang=EN-GB>Extending work from MediaEval Predicting Media Memorability task<o:p></o:p></span></li><li class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l2 level1 lfo3'><span lang=EN-GB>Cross- and multilingual aspects in Computational Memorability<o:p></o:p></span></li><li class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l2 level1 lfo3'><span lang=EN-GB>Evaluation and resources for Computational Memorability<o:p></o:p></span></li><li class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l2 level1 lfo3'><span lang=EN-GB>Computational memorability prediction based on physiological data (e.g.: EEG data)<o:p></o:p></span></li></ul><p><span lang=EN-GB>The contributions to this special session are regular short papers (only) as 4 pages, plus additional pages for the list of references. The review process is single-blind, meaning authors do not have to anonymise their submissions. <o:p></o:p></span></p><p><b><span lang=EN-GB>Important dates:</span></b><span lang=EN-GB><br>Paper submission: April 12, 2023<br>Notification of acceptance: June 1, 2023<br>Camera ready paper: June 15, 2023<br>Conference dates: September 20-22, 2023<o:p></o:p></span></p><p><b><span lang=EN-GB>Organisers: </span></b><span lang=EN-GB><o:p></o:p></span></p><ul type=disc><li class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l0 level1 lfo6'><span lang=EN-GB>Alba García Seco de Herrera, University of Essex (<a href="mailto:alba.garcia@essex.ac.uk" target="_blank">alba.garcia@essex.ac.uk</a>) <o:p></o:p></span></li><li class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l0 level1 lfo6'><span lang=EN-GB>Mihai Gabriel Constantin, University Politehnica of Bucharest (<a href="mailto:mihai.constantin84@upb.ro" target="_blank">mihai.constantin84@upb.ro</a>) <o:p></o:p></span></li><li class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l0 level1 lfo6'><span lang=EN-GB>Alan Smeaton, Dublin City University (<a href="mailto:alan.smeaton@dcu.ie" target="_blank">alan.smeaton@dcu.ie</a>)<o:p></o:p></span></li></ul><pre><span lang=EN-GB> <o:p></o:p></span></pre></div></div></div></div></div></div></div></div></body></html>