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<div style="margin: 0px">[Apologies for multiple copies due to cross-posting. Please forward to colleagues who might be interested]<br>
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<span style="color:rgb(0,0,0); font-family:Arial; font-size:12pt; font-weight:700">First Large Scale Holistic Video Understanding Workshop @ICCV’19</span><br>
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<a href="https://holistic-video-understanding.github.io/workshops/iccv2019.html"><span style="font-size:12pt; font-family:Arial; color:#1155cc; font-weight:700; text-decoration:underline">https://holistic-video-understanding.github.io/workshops/iccv2019.html</span></a></p>
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<span style="font-size:12pt; font-family:Arial; color:#000000; font-weight:400">Date: October 27, 2019 </span></p>
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<span style="font-size:12pt; font-family:Arial; color:#000000; font-weight:400">PAPER SUBMISSION IS NOW OPEN!</span></p>
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<span style="font-size:12pt; font-family:Arial; color:#000000; font-weight:400">PAPER and ABSTRACT SUBMISSION DEADLINE: August 1, 2019</span></p>
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<span style="font-size:12pt; font-family:Arial; color:#000000; font-weight:400">ACCEPTANCE NOTIFICATION: August 15, 2019</span></p>
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<span style="font-size:12pt; font-family:Arial; color:#000000; font-weight:400">Please submit papers via CMT:
</span><a href="https://cmt3.research.microsoft.com/HVU2019/"><span style="font-size:12pt; font-family:Arial; color:#1155cc; font-weight:700; text-decoration:underline">https://cmt3.research.microsoft.com/HVU2019/</span></a></p>
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<span style="font-size:12pt; font-family:Arial; color:#000000; font-weight:400">WORKSHOP REGISTRATION: In conjunction with ICCV’19</span></p>
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<span style="font-size:12pt; font-family:Arial; color:#000000; font-weight:400">*Best Paper and Best Poster Awards will be granted.</span></p>
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<span style="font-size:12pt; font-family:Arial; color:#000000; font-weight:700">OVERVIEW:</span></p>
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<span style="font-size:12pt; font-family:Arial; color:#000000; background-color:#ffffff; font-weight:400">In the last years, we have seen tremendous progress in the capabilities of computer systems to classify video clips taken from the Internet or to analyze
human actions in videos. There are lots of works in video recognition field focusing on specific video understanding tasks, such as action recognition, scene understanding, etc. There have been great achievements in such tasks, however, there has not been
enough attention toward the holistic video understanding task as a problem to be tackled. Current systems are expert in some specific fields of the general video understanding problem. However, for real-world applications, such as, analyzing multiple concepts
of a video for video search engines and media monitoring systems or providing an appropriate definition of the surrounding environment of a humanoid robot, a combination of current state-of-the-art methods should be used. Therefore, in this workshop, we intend
to introduce holistic video understanding as a new challenge for the video understanding efforts. This challenge focuses on the recognition of scenes, objects, actions, attributes, and events in the real world user-generated videos. To be able to address such
tasks, we also introduce our new dataset named Holistic Video Understanding (HVU dataset) that is organized hierarchically in a semantic taxonomy of holistic video understanding. Almost all of the real-world conditioned video datasets are targeting human action
or sport recognition. So our new dataset can help the vision community and bring more attention to bring more interesting solutions for holistic video understanding. The workshop is tailored to bringing together ideas around multi-label and multi-task recognition
of different semantic concepts in the real world videos. And the research efforts can be tried on our new dataset. HVU Dataset:
</span><a href="https://github.com/holistic-video-understanding/Mini-HVU"><span style="font-size:12pt; font-family:Arial; color:#1155cc; background-color:#ffffff; font-weight:700; text-decoration:underline">https://github.com/holistic-video-understanding/Mini-HVU</span></a></p>
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<span style="font-size:12pt; font-family:Arial; color:#000000; font-weight:700">Topics:</span></p>
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<span>Large scale video understanding</span></p>
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<span>Multi-Modal learning from videos</span></p>
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<span>Multi-concept recognition from videos</span></p>
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<span>Multi-task deep neural networks for videos</span></p>
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<span>Learning holistic representation from videos</span></p>
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<span>Weakly supervised learning from web videos</span></p>
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<span>Object, scene and event recognition from videos</span></p>
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<span>Unsupervised video visual representation learning</span></p>
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<span>Unsupervised and self-supervised learning with videos</span></p>
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<span style="font-size:12pt; font-family:Arial; color:#000000; font-weight:700">INVITED SPEAKERS:</span></p>
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<span>Rahul Sukthankar (Google AI, CMU)</span></p>
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<span>Kristen Grauman (U. Texas at Austin, Facebook AI) - TBC</span></p>
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<span>Carl Vondrick (Columbia University)</span></p>
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<span>Juan Carlos Niebles (Stanford University) -TBC</span></p>
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<span>Manohar Paluri (Facebook AI)</span></p>
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<span style="margin:0px; font-weight:700; font-size:12pt; font-family:Arial">SPONSORERS:</span></p>
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<span style="margin:0px">Facebook AI Research</span></p>
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<span style="margin:0px">Sensifai</span></p>
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<span style="font-size:12pt; font-family:Arial; color:#000000; font-weight:400">For questions about the HVU workshop, please contact
</span><a href="mailto:sharma.vivek@live.in"><span style="font-size:12pt; font-family:Arial; color:#1155cc; font-weight:400; text-decoration:underline">sharma.vivek@live.in</span></a><span style="font-size:12pt; font-family:Arial; color:#000000; font-weight:400">.
Also, follow HVU on Twitter for the latest news: @LSHVU</span></p>
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<span style="font-size:12pt; font-family:Arial; color:rgb(0,0,0)">Organizers</span><span style="font-weight:400; font-size:12pt; font-family:Arial; color:rgb(0,0,0)">:</span></p>
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<span style="font-size:12pt; font-family:Arial; color:#000000; font-weight:400">Vivek Sharma, KIT, MIT</span></p>
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<span style="font-size:12pt; font-family:Arial; color:#000000; font-weight:400">Mohsen Fayyaz, University of Bonn</span></p>
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<span style="font-size:12pt; font-family:Arial; color:#000000; font-weight:400">Ali Diba, KU Leuven</span></p>
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<span style="font-size:12pt; font-family:Arial; color:#000000; font-weight:400">Manohar Paluri, Facebook AI</span></p>
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<span style="font-size:12pt; font-family:Arial; color:#000000; font-weight:400">Juergen Gall, University of Bonn</span></p>
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<span style="font-size:12pt; font-family:Arial; color:#000000; font-weight:400">Rainer Stiefelhagen, KIT</span></p>
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<span style="font-size:12pt; font-family:Arial; color:#000000; font-weight:400">Luc Van Gool, ETH Zurich & KU Leuven</span></p>
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<span style="font-size:12pt; font-family:Arial; color:#000000; font-weight:400">best, Vivek </span></p>
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<span style="margin:0px; font-size:12pt; font-family:"Times New Roman",Times,serif; background-color:rgb(255,255,255)">M.Sc. Vivek Sharma,</span><br style="font-family:Calibri,Arial,Helvetica,sans-serif; background-color:rgb(255,255,255)">
<span style="margin:0px; font-size:12pt; font-family:"Times New Roman",Times,serif; background-color:rgb(255,255,255)">Karlsruhe Institute of Technology (KIT), Germany</span><br style="font-family:Calibri,Arial,Helvetica,sans-serif; background-color:rgb(255,255,255)">
<span style="margin:0px; font-family:"Times New Roman",Times,serif; background-color:rgb(255,255,255)">Massachusetts</span><span style="font-family:"Times New Roman",Times,serif; background-color:rgb(255,255,255); display:inline!important"><span> </span></span><span style="margin:0px; font-family:"Times New Roman",Times,serif; background-color:rgb(255,255,255)">Institute</span><span style="font-family:"Times New Roman",Times,serif; background-color:rgb(255,255,255); display:inline!important"><span> </span></span><span style="margin:0px; font-family:"Times New Roman",Times,serif; background-color:rgb(255,255,255)">of</span><span style="font-family:"Times New Roman",Times,serif; background-color:rgb(255,255,255); display:inline!important"><span> </span></span><span style="margin:0px; font-family:"Times New Roman",Times,serif; background-color:rgb(255,255,255)">Technology</span><span style="font-family:"Times New Roman",Times,serif; background-color:rgb(255,255,255); display:inline!important"><span> </span>(MIT),
USA</span><br style="font-family:Calibri,Arial,Helvetica,sans-serif; background-color:rgb(255,255,255)">
<span style="margin:0px; font-size:12pt; font-family:"Times New Roman",Times,serif; background-color:rgb(255,255,255)"><span style="margin:0px">Web:</span><span style="margin:0px"><span> <a href="http://media.mit.edu/~vvsharma" id="LPlnk183775">http://media.mit.edu/~vvsharma</a></span></span></span><br>
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