CVPR Workshop 2021

This Workshop focuses on Efficient Deep Learning For Computer Vision.

Workshop Overview Official Website

  • Computer Vision research has given little consideration to speed or computation time, and even less to constraints such as power/energy, memory footprint and model size.
  • Nevertheless, addressing all of these metrics is essential if advances in Computer Vision are going to be widely available on mobile and AR/VR devices.
  • This workshop will focus on efficient deep learning algorithms, models, and systems for computer vision.

2021 ICCV Workshop on Low-Power Computer Vision Organizing Committee

Ming-Ching Chang

University at Albany - SUNY

Shu-Ching Chen

Florida International University

Yiran Chen

ACM Speical Interest Group on Design AutomationDuke University

Callie Hao

Georgia Institute of Technology

Xiao Hu

manage lpcv.ai websitePurdue student

Mark Liao

Academia Sinica, Taiwan

Yung-Hsiang Lu

ChairPurdue

Naveen Purushotham

Xilinx Inc.

Mei-Ling Shyu

IEEE Multimedia Technical CommitteeMiami University

Joseph Spisak

Facebook

George K. Thiruvathukal

Loyola University Chiicago

Xuefeng Xiao

ByteDance Inc

Wei Zakharov

Purdue University

About LPCVC

The Low-Power Computer Vision Challenge is an annual competition started in 2015.


Motivation

Computer vision technologies have made impressive progress in recent years, but often at the expense of increasingly complex models needing more and more computational and storage resources.


Our Aim

This workshop aims to improve the energy efficiency of computer vision for running on systems with stringent resource constraints.


Our Plan

This workshop will discuss the state of the art of low-power computer vision, challenges in creating efficient vision solutions, promising technologies that can achieve the goals, methods to acquire and label data, benchmarks and metrics to evaluate progress and success.


Gallery

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Sponsors

Special Interest Group on Design Automation

*Any opinions, findings, and conclusion or recommendations expressed in this material are those of the organizers and do not necessarily reflect the view of the sponsors.

Contact Us

Address

Yung-Hsiang Lu
School of Electrical and Computer Engineering
Electrical Engineering Building
465 Northwestern Ave
West Lafayette, IN 47907-2035

Phone Number

+1 765 494-2668