MAI 2023 : CVPR 2023 Mobile AI workshop and challenges
Call For Papers
MAI: Mobile AI workshop and challenges 2023
In conjunction with CVPR 2023
Contact: radu.timofte [at] uni-wuerzburg.de
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, 2018, 2019, 2020, 2021, and 2022), CLIC (2018, 2019, 2020, 2021, 2022), PIRM (2018) and AIM (2019, 2020, 2021, 2022) workshops.
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
A paper submission has to be in English, in pdf format, and at most 8 pages (excluding references) in CVPR style.
The review process is double blind.
Accepted and presented papers will be published after the conference in the 2023 CVPR Workshops Proceedings.
Author Kit: https://media.icml.cc/Conferences/CVPR2023/cvpr2023-author_kit-v1_1-1.zip
Submission site: https://cmt3.research.microsoft.com/MAI2023
● Regular Papers Submission Deadline: March 10, 2023
● Decisions: April 05, 2023
● Camera Ready Deadline: April 13, 2023
● Learned Smartphone ISP
● Image Denoising
● HDR Image Processing
● Image Super-Resolution
● Video Super-Resolution
● Depth Estimation
To learn more about the challenges, to participate in the challenges, and to access the data everybody is invited to check the Mobile AI 2023 web page:
To learn more about the challenges and to participate:
● Release of train data: April(?), 2023
● Validation server online: April(?), 2023
● Competitions end: (?), 2023
● Andrey Ignatov ( ETH Zurich)
● Radu Timofte ( University of Wurzburg and ETH Zurich)
● Luc Van Gool ( KU Leuven and ETH Zurich)
● Cheng-Ming Chiang ( MediaTek Inc.)
● Hsien-Kai Kuo ( MediaTek)
● Kim Byeoung-su ( Samsung Electronics Co., Ltd.)
● Gaurav Arora ( Synaptics Inc.)
● Abdel Younes ( Synaptics Inc.)
● David Plowman ( Raspberry Pi (Trading) Ltd.)
● Eirikur Agustsson ( Google)
● Chiu Man Ho ( OPPO)
● Zibo Meng ( OPPO)