Deploying Image Deblurring across Mobile Devices: A Perspective of Quality and Latency

04/27/2020
by   Cheng-Ming Chiang, et al.
4

Recently, image enhancement and restoration have become important applications on mobile devices, such as super-resolution and image deblurring. However, most state-of-the-art networks present extremely high computational complexity. This makes them difficult to be deployed on mobile devices with acceptable latency. Moreover, when deploying to different mobile devices, there is a large latency variation due to the difference and limitation of deep learning accelerators on mobile devices. In this paper, we conduct a search of portable network architectures for better quality-latency trade-off across mobile devices. We further present the effectiveness of widely used network optimizations for image deblurring task. This paper provides comprehensive experiments and comparisons to uncover the in-depth analysis for both latency and image quality. Through all the above works, we demonstrate the successful deployment of image deblurring application on mobile devices with the acceleration of deep learning accelerators. To the best of our knowledge, this is the first paper that addresses all the deployment issues of image deblurring task across mobile devices. This paper provides practical deployment-guidelines, and is adopted by the championship-winning team in NTIRE 2020 Image Deblurring Challenge on Smartphone Track.

READ FULL TEXT

page 4

page 7

research
08/31/2022

ELSR: Extreme Low-Power Super Resolution Network For Mobile Devices

With the popularity of mobile devices, e.g., smartphone and wearable dev...
research
08/24/2023

MOFA: A Model Simplification Roadmap for Image Restoration on Mobile Devices

Image restoration aims to restore high-quality images from degraded coun...
research
10/22/2019

Notable Site Recognition on Mobile Devices using Deep Learning with Crowd-sourced Imagery

In this work we design a mobile system that is able to automatically rec...
research
07/03/2023

Squeezing Large-Scale Diffusion Models for Mobile

The emergence of diffusion models has greatly broadened the scope of hig...
research
07/23/2018

CNN-based Facial Affect Analysis on Mobile Devices

This paper focuses on the design, deployment and evaluation of Convoluti...
research
04/21/2023

Speed Is All You Need: On-Device Acceleration of Large Diffusion Models via GPU-Aware Optimizations

The rapid development and application of foundation models have revoluti...
research
12/15/2022

Real-Time Neural Light Field on Mobile Devices

Recent efforts in Neural Rendering Fields (NeRF) have shown impressive r...

Please sign up or login with your details

Forgot password? Click here to reset