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<span>Apologies for cross-posting<br></span><div><span>*******************************</span></div><div><span><br></span></div><div><span></span></div><div><div><span><span>CALL</span></span> FOR <span><span>PAPERS</span></span> & <span><span>CALL</span></span> FOR PARTICIPANTS IN CHALLENGES</div><div><br></div><div>3<span>rd <span class="gmail-il">Mobile</span> <span class="gmail-il">AI</span> <span>workshop and challenges on<span><span><br></span></span></span></span></div><div><span><span><span><span>learned ISP, denoising, HDR, image/video super-resolution, depth estimation, validated on <span class="gmail-il">mobile</span> hardware</span></span></span></span><br><span>In</span> conjunction with <span class="gmail-il">CVPR</span> <span><span><span><span class="gmail-il">2023</span></span></span></span>, 18th of June, Vancouver, Canada<br></div><div><br></div><div>
<div><div><div>Website:
https://<span class="gmail-il">ai</span>-<a href="http://benchmark.com/workshops/mai/">benchmark.com/workshops/mai/</a><span class="gmail-il">2023</span>/
</div><div><br></div><div>TOPICS</div><div><br></div><div style="margin-left:40px">
● Efficient deep learning models for <span class="gmail-il">mobile</span> devices
<br>● Artifacts removal from <span class="gmail-il">mobile</span> photos/videos
<br>● General smartphone photo/video enhancement
<br>● RAW camera image/video processing
<br>● Deep learning applications for <span class="gmail-il">mobile</span> camera ISPs
<br>● Image/video super-resolution on low-power hardware
<br>● Portrait segmentation / bokeh effect rendering
<br>● Depth estimation w/o multiple cameras
<br>● Perceptual image manipulation on <span class="gmail-il">mobile</span> devices
<br>● Activity recognition using smartphone sensors
<br>● Image/sensor based identity recognition
<br>● Fast image classification / object detection algorithms
<br>● NLP models optimized for <span class="gmail-il">mobile</span> inference
<br>● Real-time semantic segmentation
<br>● Low-power machine learning inference
<br>● Machine learning and deep learning frameworks for <span class="gmail-il">mobile</span> devices
<br>● <span class="gmail-il">AI</span> performance evaluation / benchmarking of <span class="gmail-il">mobile</span> and IoT hardware
<br>● Studies and applications of the above problems
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<div><div>SUBMISSION<div><br></div><div>
<div>A <span><span>paper</span></span> submission has to be in English, in pdf format, and at most 8
pages (excluding references) in CVPR style. <br></div><div>
<a href="https://cvpr2023.thecvf.com/Conferences/2023/AuthorGuideliness" target="_blank">https://cvpr2023.thecvf.com/Conferences/2023/AuthorGuidelines</a></div><div>The review process is double blind. <br>
</div><div>Accepted and presented <span><span>papers</span></span> will be published after the conference
in the 2023 CVPR Workshops Proceedings.
<br>
<br>Author Kit:
<a href="https://media.icml.cc/Conferences/CVPR2023/cvpr2023-author_kit-v1_1-1.zip" target="_blank">https://media.icml.cc/Conferences/CVPR2023/cvpr2023-author_kit-v1_1-1.zip</a>
</div><div>Submission site: <a href="https://cmt3.research.microsoft.com/MAI2023">https://cmt3.research.microsoft.com/MAI2023</a>
</div></div></div></div><div><br></div>
</div><div>WORKSHOP DATES</div><div><br></div><div>
<div><div style="margin-left:40px">
● <b><span>Regular Papers</span> submission deadline: February 28, <span><span><span class="gmail-il">2023</span></span></span></b><span><span> </span></span><b><span><span><br></span></span></b></div><div style="margin-left:40px"><span><span></span></span></div><div style="margin-left:40px"><span><span><span class="gmail-il"></span></span></span></div><div style="margin-left:40px"><span><span><br></span></span></div>
<div><div>CHALLENGES (TBU)<br></div><div style="margin-left:40px"><br></div><div style="margin-left:40px">
● <b>Learned Smartphone ISP</b><br> ● <b>Image Denoising</b> <br> ● <b>HDR Image Processing</b> <br> ● <b>Image Super-Resolution</b><br> ● <b>Video Super-Resolution</b> <br> ● <b>Depth Estimation</b> <br>
</div></div><div><br></div><div>To learn more about the challenges, to participate <span>in</span> the challenges,
<span>and</span> to access the data everybody is invited to check the <span><span><span class="gmail-il">Mobile</span> <span class="gmail-il">AI</span></span></span> <span class="gmail-il">2023</span> web page:</div><div>
https://<span class="gmail-il">ai</span>-<a href="http://benchmark.com/workshops/mai/">benchmark.com/workshops/mai/</a><span class="gmail-il">2023</span>/
<div><div><br></div><div>For those interested in image and video restoration,
enhancement, manipulation, super-resolution without specific <span class="gmail-il">mobile</span>
hardware constraints we refer to the CVPR23<b> NTIRE Workshop and Challenges:</b></div>
<a href="https://cvlai.net/ntire/2023/" target="_blank">https://cvlai.net/ntire/2023/</a>
<div><br></div><div>
CHALLENGES DATES (TBU)<br><div>
<br><div style="margin-left:40px">● Release of train data: March 21, <span><span><span><span class="gmail-il">2023</span></span></span></span><br>● <b>Competitions end: May 31, <span><span><span><span class="gmail-il">202</span></span></span></span></b><span><span><span></span></span></span><b><span><span><span><b><span><span>3<br></span></span></b></span></span></span></b></div><div style="margin-left:40px"><b><span><span><span><br></span></span></span></b></div><b><span><span><span></span></span></span></b><span><span><span></span></span></span>Website:
https://<span class="gmail-il">ai</span>-<a href="http://benchmark.com/workshops/mai/">benchmark.com/workshops/mai/</a><span class="gmail-il">2023</span>/</div></div></div></div></div></div>
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