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<span>Apologies for multiple postings<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>MAI 6<span>th <span><span>Mobile</span></span> <span><span>AI</span></span> <span><span>workshop</span> and challenges on<span><span><br></span></span></span></span></div><div>Efficient
LLMs, Efficient Stable Diffusion, Image/Video Super-Resolution,
Efficient ViTs, Image Denoising, Bokeh Effect Rendering, Photo
Enhancement, Learned Smartphone ISP
</div><div><span><span><span><span>validated on <span><span>mobile</span></span> hardware</span></span></span></span><br><span>In</span> conjunction with <span>CVPR</span> <span><span><span><span>2026</span></span></span></span>, June 3-7, Denver, US<br></div><div><br></div><div>
<div><div><div>Website:
https://<span><span>ai</span></span>-<a href="http://benchmark.com/">benchmark.com/</a><span>workshops</span>/mai/<span>2026</span>/ <br></div><div>Contact: <a href="mailto:ihnatova@ethz.ch">ihnatova@ethz.ch</a></div><div><br></div><div>TOPICS</div><div><br></div><div style="margin-left:40px">
● Efficient deep learning models for <span><span>mobile</span></span> devices
<br>● Artifacts removal from <span><span>mobile</span></span> photos/videos
<br>● General smartphone photo/video enhancement
<br>● RAW camera image/video processing
<br>● Deep learning applications for <span><span>mobile</span></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><span>mobile</span></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><span>mobile</span></span> inference
<br>● Real-time semantic segmentation
<br>● Low-power machine learning inference
<br>● Machine learning and deep learning frameworks for <span><span>mobile</span></span> devices
<br>● <span><span>AI</span></span> performance evaluation / benchmarking of <span><span>mobile</span></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 <span>CVPR</span> style. <br></div><div>
<a href="https://cvpr.thecvf.com/Conferences/2026/AuthorGuidelines" target="_blank">https://cvpr.thecvf.com/Conferences/2026/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 <span>2026</span> <span>CVPR</span> Workshops Proceedings.
<br>
<br>Author Kit: <a href="https://github.com/cvpr-org/author-kit/archive/refs/tags/CVPR2026-v1(latex).zip" target="_blank">https://github.com/cvpr-org/author-kit/archive/refs/tags/CVPR2026-v1(latex).zip</a></div><div></div><div></div>
<div><div><div>Submission site: <a href="https://cmt3.research.microsoft.com/AIMWC2026">https://cmt3.research.microsoft.com/AIMWC2026</a></div><div><br></div></div></div></div></div></div><div><br></div>
</div><div><span>WORKSHOP</span> DATES</div><div><br></div><div>
<div><div style="margin-left:40px">
● <b><span>Regular Papers</span> submission deadline: March 10, <span><span><span>202</span></span></span><span><span>6<br></span></span></b></div><div style="margin-left:40px"><span><span></span></span></div><div style="margin-left:40px"><span><span><span></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>● Image Super-Resolution
<br>● Efficient LLMs
<br>● Efficient Stable Diffusion
<br>● Video Super-Resolution
<br>● Efficient ViTs for <span>Mobile</span>
<br>● Image Denoising
<br>● Bokeh Effect Rendering
<br>● RGB Photo Enhancement
<br>● Learned Smartphone ISP
</b> </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><span>Mobile</span></span> <span><span>AI</span></span></span></span> <span>2026</span> web page:</div><div>
https://<span><span>ai</span></span>-<a href="http://benchmark.com/">benchmark.com/</a><span>workshops</span>/mai/<span>2026</span>/
<div><div><br></div><div>For those interested in image and video restoration,
enhancement, manipulation, super-resolution, rendering, deepfake detection, quality assessment without specific <span><span>mobile</span></span>
hardware constraints we refer to the <b>CVPR26 NTIRE <span>Workshop</span> and Challenges:</b></div>
<a href="https://www.cvlai.net/ntire/2026/">https://www.cvlai.net/ntire/2026/</a>
<div><br></div><div>
CHALLENGES DATES (TBU)<br><div>
<br><div style="margin-left:40px">● Release of train data: February 1, <span><span><span><span>2026</span></span></span></span><br>● <b>Competitions end: March 17, 2026<br></b></div><b><span><span><span></span></span></span></b><span><span><span></span></span></span><br></div><div>Website:
https://<span><span>ai</span></span>-<a href="http://benchmark.com/">benchmark.com/</a><span>workshops</span>/mai/<span>2026</span>/</div></div></div></div></div></div>
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