MAI: Mobile AI workshop and challenges 2026
In conjunction with CVPR 2026

https://ai-benchmark.com/workshops/mai/2026/
Contact: ihnatova [at] ethz.ch; radu.timofte [at] uni-wuerzburg.de

Scope

Over the past years, mobile AI-based applications are becoming more and more ubiquitous. Various deep learning models can now be found on any mobile device starting from smartphones running portrait segmentation, image enhancement, face recognition and natural language processing models, to IoT platforms performing real-time image classification or smart-TV boards coming with sophisticated image super-resolution algorithms. The performance of mobile NPUs and DSPs is also increasing dramatically, making it possible to run complex deep learning models and to achieve fast runtime in the majority of tasks.

While many research papers targeted at efficient deep learning models have been proposed recently, the evaluation of the obtained solutions is usually happening on desktop CPUs and GPUs, making it nearly impossible to estimate the actual inference time and memory consumption on real mobile hardware. To address this problem, we introduce the first Mobile AI Workshop, where all solutions and deep learning models will be evaluated on the actual mobile AI accelerators.

The workshop will consist of the three main parts, including: 1) a detailed overview of deep learning inference on mobile platforms, 2) workshop challenges where the participants can get the actual hands-on experience while solving several computer vision tasks and evaluating their solutions on mobile devices, and 3) presentations from mobile SoC vendors covering several important aspects of mobile AI inference.

To ensure that the participants get the most recent and actual information on mobile-related AI tasks, the workshop is designed in collaboration with several major mobile SoC vendors, including Qualcomm, Samsung, Huawei, MediaTek, and Synaptics.

This workshop also builds upon the success of the previous computer vision competitions and is organized by people associated with the NTIRE (CVPR 2017-2026), CLIC (2018-2024), PIRM (2018) and AIM (2019-2025) workshops.

Topics

Papers addressing the topics covering efficient deep learning for mobile devices, mobile-based vision / natural language processing / performance evaluation are invited. The topics include, but are not limited to:

● Efficient deep learning models for mobile devices
● Artifacts removal from mobile photos/videos
● General smartphone photo/video enhancement
● RAW camera image/video processing
● Deep learning applications for mobile camera ISPs
● Image/video super-resolution on low-power hardware
● Portrait segmentation / bokeh effect rendering
● Depth estimation w/o multiple cameras
● Perceptual image manipulation on mobile devices
● Activity recognition using smartphone sensors
● Image/sensor based identity recognition
● Fast image classification / object detection algorithms
● NLP models optimized for mobile inference
● Real-time semantic segmentation
● Low-power machine learning inference
● Machine learning and deep learning frameworks for mobile devices
● AI performance evaluation / benchmarking of mobile and IoT hardware
● Studies and applications of the above problems


Submission

A paper submission has to be in English, in pdf format, and at most 8 pages (excluding references) in CVPR style.
https://cvpr.thecvf.com/Conferences/2026/AuthorGuidelines
Author Kit: https://github.com/cvpr-org/author-kit/archive/refs/tags/CVPR2026-v1(latex).zip
Submission site: https://cmt3.research.microsoft.com/MAIWC2026
The review process is double blind.

Accepted and presented papers will be published after the conference in the CVPR Workshops Proceedings on by IEEE (http://www.ieee.org) and Computer Vision Foundation (https://openaccess.thecvf.com/menu).


Workshop Dates

● Regular Papers submission deadline: March 10, 2026
● Challenge Papers submission deadline: March 24, 2026
● Papers reviewed elsewhere submission deadline: March 24, 2026
● Decisions: March 31, 2026
● Camera Ready Deadline: April 10, 2026


Challenges

● Image Super-Resolution
● Efficient LLMs
● Efficient Stable Diffusion
● Video Super-Resolution
● Efficient ViTs for Mobile
● Image Denoising
● Bokeh Effect Rendering
● RGB Photo Enhancement
● Learned Smartphone ISP

To learn more about the challenges, to participate in the challenges, and to access the data everybody is invited to check the Mobile AI 2026 web page:
https://ai-benchmark.com/workshops/mai/2026/


Participation

To learn more about the challenges and to participate:
https://ai-benchmark.com/workshops/mai/2026/


Challenges Dates

● Release of train data: February 1, 2026
● Validation server online: February 10, 2026
● Competitions end: March 17(?), 2026


Contact

Email: ihnatova [at] ethz.ch
Website: https://ai-benchmark.com/workshops/mai/2026/