Connectionists: CFP: CVPR 2021 Mobile AI workshop and challenges

[Radu Timofte]

 Apologies for cross-posting
*******************************

CALL FOR PAPERS  & CALL FOR PARTICIPANTS IN 7 CHALLENGES

1st Mobile AI workshop and challenges on
learned ISP, denoising, HDR, image/video super-resolution, depth
estimation, scene detection
In conjunction with CVPR 2021, 20th of June, Nashville, USA (VIRTUAL).

Website: https://ai-benchmark.com/workshops/mai/2021/

TOPICS

● 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.
http://cvpr2021.thecvf.com/node/33
The review process is double blind.
Accepted and presented papers will be published in the CVPR 2021 Workshops
Proceedings.

Author Kit:
http://cvpr2021.thecvf.com/sites/default/files/2020-09/cvpr2021AuthorKit_2.zip
Submission site: https://cmt3.research.microsoft.com/MAI2021

WORKSHOP DATES

● *Regular Papers Submission Deadline: March 05, 2021*
● Challenge Papers Submission Deadline: April 2, 2021

CHALLENGES

● *Learned Smartphone ISP* (Evaluation platform: MediaTek Dimensity APU) -
Powered by MediaTek
● *Image Denoising* (Eval. platform: Exynos Mali GPU) - Powered by Samsung
● *HDR Image Processing* (Eval. platform: Kirin DaVinci NPU) - Powered by
Huawei
● *Image Super-Resolution* (Eval. platform: Synaptics Dolphin NPU) -
Powered by Synaptics
● *Video Super-Resolution* (Eval. platform: Snapdragon Adreno GPU) -
Powered by OPPO
● *Depth Estimation* (Eval. platform: Raspberry Pi 4) - Powered by
Raspberry Pi
● * Camera Scene Detection* (Eval. platform: Apple Bionic) - Powered by CVL

To learn more about the challenges, to participate in the challenges, and
to access the data everybody is invited to check the Mobile AI 2021 web
page:
https://ai-benchmark.com/workshops/mai/2021/

For those interested in restoration, enhancement, manipulation,
classification without specific mobile hardware constraints we refer to the
CVPR21* NTIRE Workshop and Challenges:*
https://data.vision.ee.ethz.ch/cvl/ntire21/

CHALLENGES DATES

● Release of train data: January 10, 2020
● *Competitions end: March 20, 2020*

ORGANIZERS (TBU)

● Andrey Ignatov ( ETH Zurich)
● Radu Timofte ( ETH Zurich)
● Luc Van Gool ( ETH Zurich and KU Leuven)
● Martti Ilmoniemi ( Huawei)
● Esin Guldogan ( Huawei)
● Tianyu Yao ( Huawei)
● 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.)
● Heewon Kim ( Seoul National University)
● Kyoung Mu Lee ( Seoul National University)
● Eirikur Agustsson ( Google)
● Chiu Man Ho ( OPPO)
● Zibo Meng ( OPPO)
● Shuhang Gu ( University of Sydney, OPPO)

SPEAKERS (TBA)

SPONSORS (TBU)

● OPPO
● Samsung
● MediaTek
● Synaptics
● Huawei
● Raspberry Pi
● CVL / ETH Zurich

Website: https://ai-benchmark.com/workshops/mai/2021/
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