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<body lang="EN-IN" link="blue" vlink="purple">
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<p class="MsoNormal"><span style="font-size:10.0pt">Dear All, </span><o:p></o:p></p>
<p class="MsoNormal"><span style="font-size:10.0pt"> </span><o:p></o:p></p>
<p class="MsoNormal"><span style="font-size:10.0pt">Posting the CFP again. Apologies for cross-posting.</span><o:p></o:p></p>
<p class="MsoNormal"><span style="font-size:10.0pt"> </span><o:p></o:p></p>
<p class="MsoNormal" align="center" style="text-align:center"><b><span style="font-size:14.0pt;color:black">CLVISION CVPR 2020: Workshop on Continual Learning in Computer Vision</span></b><o:p></o:p></p>
<div>
<p class="MsoNormal" align="center" style="text-align:center"><a href="https://sites.google.com/view/clvision2020/overview"><b><span style="font-size:10.0pt">https://sites.google.com/view/clvision2020</span></b></a><o:p></o:p></p>
</div>
<p class="MsoNormal" align="center" style="text-align:center"><span style="font-size:10.0pt;color:black"> </span><o:p></o:p></p>
<div>
<p class="MsoNormal" style="margin-bottom:12.0pt"><span style="font-size:10.0pt;color:black"> </span><o:p></o:p></p>
</div>
<div>
<p class="MsoNormal"><b><span style="font-size:10.0pt;color:black">OVERVIEW</span></b><o:p></o:p></p>
</div>
<div>
<p class="MsoNormal"><span style="font-size:10.0pt;color:black"> </span><o:p></o:p></p>
</div>
<div>
<p style="text-align:justify"><span style="font-size:10.0pt;color:black">During the past few years we have witnessed a renewed and growing attention to Continuous Learning (CL). The interest in CL is essentially twofold. From the artificial intelligence perspective,
CL can be seen as another important step towards the grand goal of creating autonomous agents which can learn continuously and acquire new and complex skills and knowledge. From a more practical perspective, CL looks particularly appealing because it enables
two important properties: adaptability and scalability. One of the key hallmarks of CL techniques is the ability to update the models by using only recent data (i.e., without accessing old data). This is often the only practical solution when learning on the
edge from high-dimensional streaming or ephemeral data, which would be impossible to keep in memory and process from scratch every time a new piece of information becomes available. Unfortunately, when (deep or shallow) neural networks are trained only on
new data, they experience a rapid overriding of their weights with a phenomenon known in the literature as
<i>catastrophic forgetting</i>.</span><o:p></o:p></p>
<p class="MsoNormal"><span style="font-size:10.0pt;color:black"> </span><o:p></o:p></p>
</div>
<div>
<p class="MsoNormal"><span style="font-size:10.0pt;color:black">To this end, the goal of the CVPR 2020 Workshop on Continual Learning (CLVISION) is to explore methods that generalize to a continuous stream of tasks, incrementally consolidating their knowledge
without interfering with previously learned information. Thus, we encourage submissions that address the problems of learning from a few examples, catastrophic forgetting and online learning, large-scale realistic benchmarks, or bio-inspired systems for continual
learning, such as memory and plasticity. In this one-day workshop, we will have regular paper presentations, invited speakers, and technical benchmark challenges to present the current state of the art, as well as the limitations and future directions for
computer vision in continual learning, arguably one of the most crucial milestones of computer vision and AI in general.
</span><o:p></o:p></p>
</div>
<div>
<p style="text-align:justify"><span style="font-size:10.0pt;color:black"> </span><o:p></o:p></p>
<p style="text-align:justify"><span style="font-size:10.0pt;color:black">We solicit paper submissions on novel methods and application scenarios of Continual Learning.</span><o:p></o:p></p>
<p class="MsoNormal" style="text-align:justify"><span style="font-size:10.0pt;color:black"> </span><o:p></o:p></p>
<p class="MsoNormal"><b><span style="font-size:10.0pt;color:black">TOPICS OF INTEREST (include but are not limited to):</span></b><o:p></o:p></p>
</div>
<div>
<p class="MsoNormal"><span style="font-size:10.0pt;color:black"> </span><o:p></o:p></p>
</div>
<div>
<ul type="disc">
<li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l5 level1 lfo1">
<b><span style="font-size:10.0pt">Continual/Lifelong learning:</span></b><span style="font-size:10.0pt"> Models that are able to adapt to new tasks without forgetting the previously-learned ones.</span><o:p></o:p></li><li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l5 level1 lfo1">
<b><span style="font-size:10.0pt">Few-shot learning:</span></b><span style="font-size:10.0pt"> Models that learn from a few examples.</span><o:p></o:p></li><li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l5 level1 lfo1">
<b><span style="font-size:10.0pt">Transfer learning:</span></b><span style="font-size:10.0pt"> Models that use new information to improve the performance in previous and novel tasks.</span><o:p></o:p></li><li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l5 level1 lfo1">
<b><span style="font-size:10.0pt">Online learning:</span></b><span style="font-size:10.0pt"> Models that can learn online.</span><o:p></o:p></li><li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l5 level1 lfo1">
<b><span style="font-size:10.0pt">Bio-inspired learning:</span></b><span style="font-size:10.0pt"> Works that take inspiration in nature to propose fundamental mechanisms for continual learning, such as memory or synaptic plasticity<b>.</b></span><o:p></o:p></li><li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l5 level1 lfo1">
<b><span style="font-size:10.0pt">Curiosity:</span></b><span style="font-size:10.0pt"> Works where the model identifies the most important pieces of information to incorporate new knowledge efficiently. Unsupervised/self-supervised models are welcome.</span><o:p></o:p></li><li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l5 level1 lfo1">
<b><span style="font-size:10.0pt">Metrics:</span></b><span style="font-size:10.0pt"> Metrics and benchmarks for continual learning of visual representations.</span><o:p></o:p></li><li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l5 level1 lfo1">
<b><span style="font-size:10.0pt">Experience replay: </span></b><span style="font-size:10.0pt">Experience replay for learning systems and robots.</span><o:p></o:p></li></ul>
<div>
<p class="MsoNormal"><span style="font-size:10.0pt;color:black">All accepted papers will be presented as posters. Two papers will be selected for oral presentation and one paper will be awarded as the best paper. </span><o:p></o:p></p>
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<p class="MsoNormal"><span style="font-size:10.0pt;color:black"> </span><o:p></o:p></p>
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<p class="MsoNormal"><b><span style="font-size:10.0pt;color:black">CLVision CHALLENGE:</span></b><o:p></o:p></p>
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<p class="MsoNormal"><span style="font-size:10.0pt;color:black"> </span><o:p></o:p></p>
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<div>
<p class="MsoNormal"><span style="font-size:10.0pt;color:black">CLVision workshop also provides a comprehensive 2-phase challenge track to thoroughly assess novel continual learning solutions in the computer vision context based on 3 different continual learning
(CL) protocols. With this challenge we aim to:</span><o:p></o:p></p>
<div>
<ul type="disc">
<li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l0 level1 lfo2">
<span style="font-size:10.0pt">Invite the research community to scale up CL approaches to natural images and possibly on video benchmarks.</span><o:p></o:p></li><li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l0 level1 lfo2">
<span style="font-size:10.0pt">Invite the community to work on solutions that can generalize over multiple CL protocols and settings (e.g. with or without a “task” supervised signal).</span><o:p></o:p></li><li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l0 level1 lfo2">
<span style="font-size:10.0pt">Provide the first opportunity for comprehensive evaluation on a shared hardware platform for a fair comparison.</span><o:p></o:p></li><li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l0 level1 lfo2">
<span style="font-size:10.0pt">Provide the first opportunity to show the generalization capabilities (over learning) of the proposed approaches on a hidden continual learning benchmark.</span><o:p></o:p></li></ul>
</div>
<div>
<p class="MsoNormal"><span style="font-size:10.0pt;color:black">More details on the CLVision Workshop Challenge can be found here:
</span><a href="https://sites.google.com/view/clvision2020/challenge"><span style="font-size:10.0pt">https://sites.google.com/view/clvision2020/challenge</span></a><span style="font-size:10.0pt;color:black">.</span><o:p></o:p></p>
</div>
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<p class="MsoNormal"><span style="font-size:10.0pt;color:black"> </span><o:p></o:p></p>
</div>
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<div>
<p class="MsoNormal"><span style="font-size:10.0pt;color:black"> </span><o:p></o:p></p>
</div>
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<p class="MsoNormal"><b><span style="font-size:10.0pt;color:black">SUBMISSION GUIDELINES:</span></b><o:p></o:p></p>
<ul type="disc">
<li class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l3 level1 lfo3">
<span style="font-size:10.0pt;color:black">The submitted manuscript should follow the
<b>CVPR 2019</b> </span><a href="http://cvpr2019.thecvf.com/submission/main_conference/author_guidelines"><span style="font-size:10.0pt">paper template</span></a><span style="font-size:10.0pt;color:black">.</span><span style="font-size:10.0pt"> Paper submission
through: </span><a href="https://cmt3.research.microsoft.com/CONTVISION2020"><b><span style="font-size:10.0pt">https://cmt3.research.microsoft.com/CONTVISION2020</span></b></a><o:p></o:p></li><li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l3 level1 lfo3">
<span style="font-size:10.0pt">The page limit </span><span style="font-size:10.0pt;color:windowtext">for a full paper
</span><span style="font-size:10.0pt">is 8 pages (excluding references) and </span>
<span style="font-size:10.0pt;color:windowtext">short-papers is 4-pages (excluding references).</span><o:p></o:p></li><li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l3 level1 lfo3">
<span style="font-size:10.0pt">We accept <b>dual</b> <b>submissions</b> to <b>CVPR 2020</b> and<b> CLVISION 2020</b>, but the manuscript must contain substantial original contents not submitted to any other conference, workshop or journal.</span><o:p></o:p></li><li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l3 level1 lfo3">
<span style="font-size:10.0pt">Submissions will be <b>rejected</b> without review if they:</span><o:p></o:p></li></ul>
<ul type="disc">
<ul type="circle">
<li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l3 level2 lfo3">
<span style="font-size:10.0pt">contain more than 8 pages (excluding references).</span><o:p></o:p></li><li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l3 level2 lfo3">
<span style="font-size:10.0pt">violate the double-blind policy or violate the dual-submission policy.</span><o:p></o:p></li></ul>
</ul>
<ul type="disc">
<li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l3 level1 lfo3">
<span style="font-size:10.0pt">The accepted papers will be linked at the workshop webpage and also in the main conference proceedings if the authors agree</span><o:p></o:p></li><li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l3 level1 lfo3">
<span style="font-size:10.0pt">Papers will be peer-reviewed under the double-blind policy.</span><o:p></o:p></li></ul>
<p class="MsoNormal"><span style="font-size:10.0pt;color:black"> </span><o:p></o:p></p>
</div>
<div>
<p class="MsoNormal"><b><span style="font-size:10.0pt;color:black">IMPORTANT DATES:</span></b><o:p></o:p></p>
</div>
<div>
<p class="MsoNormal"><span style="font-size:10.0pt;color:black"> </span><o:p></o:p></p>
</div>
<div>
<p class="MsoNormal"><span style="font-size:10.0pt;color:black">Workshop paper submission deadline:
<b>March 20th 2020</b> (11:59 pm Pacific Time) </span><o:p></o:p></p>
<ul type="disc">
<li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l2 level1 lfo4">
<span style="font-size:10.0pt">Notification to authors:<b> 2nd April 2020</b></span><o:p></o:p></li><li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l2 level1 lfo4">
<span style="font-size:10.0pt">Camera-ready deadline: <b>10th April 2020</b> (11:59 pm Pacific Time)</span><o:p></o:p></li><li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l2 level1 lfo4">
<span style="font-size:10.0pt">Workshop date: <b>June 14, 2020 </b></span><o:p></o:p></li></ul>
<p class="MsoNormal"><span style="font-size:10.0pt;color:black"><br>
<b>INVITED SPEAKERS:</b></span><o:p></o:p></p>
</div>
<div>
<ul type="disc">
<li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l4 level1 lfo5">
<span style="font-size:10.0pt">Dr Razvan Pascanu, DeepMind.</span><o:p></o:p></li><li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l4 level1 lfo5">
<span style="font-size:10.0pt">Prof Chelsea Finn, Assistant Professor at Stanford University.</span><o:p></o:p></li><li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l4 level1 lfo5">
<span style="font-size:10.0pt">Prof Cordelia Schmid INRIA Research Director, Head of THOTH Project Team.</span><o:p></o:p></li><li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l4 level1 lfo5">
<span style="font-size:10.0pt">Prof David Maltoni, Professor, Universita Di Bologna.</span><o:p></o:p></li><li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l4 level1 lfo5">
<span style="font-size:10.0pt">Prof Christopher Kanan, PAIGE, RIT and CornellTech.
</span><o:p></o:p></li><li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l4 level1 lfo5">
<span style="font-size:10.0pt">Prof Gemma Roig, Ass. Professor at SUTD, MIT. </span>
<o:p></o:p></li><li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l4 level1 lfo5">
<span style="font-size:10.0pt">Subutai Ahmad, VP Research, Numenta. </span><o:p></o:p></li></ul>
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<p class="MsoNormal"><b><span style="font-size:10.0pt;color:black"><br>
ORGANIZERS</span></b><span style="font-size:10.0pt;color:black">: </span><o:p></o:p></p>
</div>
<div>
<ul type="disc">
<li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l1 level1 lfo6">
<span style="font-size:10.0pt">Pau Rodriguez, Element AI.</span><o:p></o:p></li><li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l1 level1 lfo6">
<span style="font-size:10.0pt">German Parisi, University of Hamburg.</span><o:p></o:p></li><li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l1 level1 lfo6">
<span style="font-size:10.0pt">David Vazquez, Element AI.</span><o:p></o:p></li><li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l1 level1 lfo6">
<span style="font-size:10.0pt">Vincenzo Lomonaco, University of Bologna. </span><o:p></o:p></li><li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l1 level1 lfo6">
<span style="font-size:10.0pt">Nikhil Churamani, University of Cambridge. </span>
<o:p></o:p></li><li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l1 level1 lfo6">
<span style="font-size:10.0pt">Zhiyuan (Brett) Chen, Google.</span><o:p></o:p></li><li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l1 level1 lfo6">
<span style="font-size:10.0pt">Marc Pickett, Google Research.</span><o:p></o:p></li></ul>
<p class="MsoNormal"><span style="font-size:10.0pt;color:black"><br>
<b>WORKSHOP WEBSITE</b></span><o:p></o:p></p>
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<p class="MsoNormal"><span style="font-size:10.0pt;color:black"> </span><o:p></o:p></p>
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<div>
<p class="MsoNormal"><a href="https://sites.google.com/view/clvision2020/overview"><b><span style="font-size:10.0pt">https://sites.google.com/view/clvision2020</span></b></a><b><span style="font-size:10.0pt;color:black">/</span></b><o:p></o:p></p>
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<p class="MsoNormal"><span style="font-size:10.0pt;color:black"> </span><o:p></o:p></p>
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<p class="MsoNormal"><span style="font-size:10.0pt;color:black"> </span><o:p></o:p></p>
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<p class="MsoNormal"><b><span style="font-size:10.0pt;color:black">PAPER SUBMISSION:</span></b><o:p></o:p></p>
</div>
<div>
<p class="MsoNormal"><span style="font-size:10.0pt;color:black"> </span><o:p></o:p></p>
</div>
<div>
<p class="MsoNormal"><a href="https://cmt3.research.microsoft.com/CONTVISION2020"><b><span style="font-size:10.0pt">https://cmt3.research.microsoft.com/CONTVISION2020</span></b></a><o:p></o:p></p>
</div>
<div>
<p class="MsoNormal"><span style="font-size:10.0pt;color:black"> </span><o:p></o:p></p>
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<p class="MsoNormal"><span style="font-size:12.0pt;color:black"> </span><o:p></o:p></p>
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<p class="MsoNormal"><span style="font-size:12.0pt;color:black"> </span><o:p></o:p></p>
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<p class="MsoNormal"><span style="font-size:12.0pt;color:black"> </span><o:p></o:p></p>
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<p class="MsoNormal"><span style="font-size:10.0pt;color:#333333">---------------------------</span><o:p></o:p></p>
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<p class="MsoNormal"><span style="font-size:10.0pt;color:#333333">Thanks and Regards</span><span style="font-size:12.0pt;color:black"><br>
</span><b><span style="font-size:10.0pt;color:#333333">Nikhil Churamani</span></b><span style="font-size:12.0pt;color:black"><br>
</span><span style="font-size:10.0pt;color:#333333">PhD Student</span><o:p></o:p></p>
</div>
<div>
<p class="MsoNormal"><span style="font-size:10.0pt;color:#333333">University of Cambridge</span><span style="font-size:12.0pt;color:black"><br>
</span><span style="font-size:10.0pt;color:#333333">Department of Computer Science and Technology</span><span style="font-size:12.0pt;color:black"><br>
</span><span style="font-size:10.0pt;color:#333333">William Gates Building</span><span style="font-size:12.0pt;color:black"><br>
</span><span style="font-size:10.0pt;color:#333333">15 JJ Thomson Avenue</span><span style="font-size:12.0pt;color:black"><br>
</span><span style="font-size:10.0pt;color:#333333">Cambridge CB3 0FD</span><span style="font-size:12.0pt;color:black"><br>
</span><span style="font-size:10.0pt;color:#333333">Phone:</span><span style="font-size:12.0pt;color:black">
</span><span style="font-size:10.0pt;color:#333333">+44 1223 767024</span><span style="font-size:12.0pt;color:black"><br>
</span><span style="font-size:10.0pt;color:#333333">Email: Nikhil DOT Churamani AT </span><a href="http://cl.cam.ac.uk" target="_blank"><span style="font-size:10.0pt;color:#333333">cl.cam.ac.uk</span></a><o:p></o:p></p>
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<p class="MsoNormal"><span style="font-size:10.0pt;color:#333333">Web: </span><a href="https://www.cl.cam.ac.uk/~nc528"><span style="font-size:10.0pt;color:#333333">https://www.cl.cam.ac.uk/~nc528</span></a><span style="color:black">
</span><o:p></o:p></p>
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