The Bright and Dark Sides of Computer Vision:
Challenges and Opportunities for Privacy and Security
(CV-COPS 2019)

Long Beach, CA

In conjunction with the 2019 IEEE Conference on Computer Vision and Pattern Recognition


Computer vision is finally working in the real world, but what are the consequences on privacy and security? For example, recent work shows that vision algorithms can spy on smartphone keypresses from meters away, steal information from inside homes via hacked cameras, exploit social media to de-anonymize blurred faces, and reconstruct images from features like SIFT. Vision could also enhance privacy and security, for example through assistive devices for people with disabilities, phishing detection techniques that incorporate visual features, and image forensic tools. Some technologies present both challenges and opportunities: biometrics techniques could enhance security but may be spoofed, while surveillance systems enhance safety but create potential for abuse.

We need to understand the potential threats and opportunities of vision to avoid creating detrimental societal effects and/or facing public backlash. Following up on last year's very successful workshops at CVPR 2017, and CVPR 2018, this workshop will continue to explore the intersection between computer vision and security and privacy to address these issues.

Call for Papers and Extended Abstracts

We welcome original research papers and extended abstracts on topics including, but not limited to:

  • Computer vision-based security and privacy attacks
  • Biometric spoofing, defenses and liveness detection
  • Impact of ubiquitous cameras on society
  • Captchas and other visual Turing tests for online security
  • Privacy of visual data
  • Privacy-preserving visual features and representations
  • Reversibility of image transformations
  • Secure/encrypted computer vision and image processing
  • Wearable camera privacy
  • Attacks against computer vision systems
  • Copyright violation detection
  • Counterfeit and forgery detection
  • Privacy implications of large-scale visual social media
  • Other relevant topics

Research papers should contain original, unpublished research, and be 4-8 pages (excluding references). Research papers will be published in the CVPR Workshop Proceedings and archived on IEEE eXplore and the Computer Vision Foundation websites.

Extended abstracts about preliminary, ongoing or published work should be up to 2 pages (including references). Extended abstracts will be published and archived on this website. Author Notification Date: TBD.
Extended Abstract Deadline: TBD.
Camera ready deadline: TBD.


David Crandall

David Crandall
Indiana University

Jan-Michael Frahm

Jan-Michael Frahm
University of North Carolina at Chapel Hill

Mario Fritz

Mario Fritz
CISPA Helmholtz Center i.G.

Apu Kapadia

Apu Kapadia
Indiana University

Vitaly Shmatikov

Vitaly Shmatikov
Cornell Tech