VFRAME researches and develops state-of-the-art computer vision technologies for human rights research and conflict zone monitoring

VFRAME is developed and maintained by Adam Harvey in Berlin with contributions from Jules LaPlace, Josh Evans, and a growing list of collaborators. VFRAME is being piloted with Mnemonic.org an organization dedicated to helping human rights defenders effectively use digital documentation of human rights violations and international crimes to support advocacy, justice and accountability.

VFRAME's image processing software is open-source (MIT licensed) and available at github.com/vframeio. Download object detection models using the Python CLI tools or try a online demo using the modelzoo.vframe.io.

 2018: Showing an early prototype of the AO-2.5RT object detector at republica:18 in Berlin
2018: Showing an early prototype of the AO-2.5RT object detector at republica:18 in Berlin
 2022: Showing a functional AO-2.5RT object detector at the United Nations Eighth Biennial Meeting of States on Small Arms and Light Weapons in partnership with Tech 4 Tracing
2022: Showing a functional AO-2.5RT object detector at the United Nations Eighth Biennial Meeting of States on Small Arms and Light Weapons in partnership with Tech 4 Tracing

Recent News and Events

Origins and Mission

The idea for VFRAME grew out of discussions at a 2017 Data Investigation Camp organized by Tactical Technology Collective in Montenegro. Through meeting with investigative journalists, human rights researchers, and digital activists from around the world it became clear that computer vision was a much needed tool in this community yet the solutions were nowhere in sight.

Since then VFRAME's mission has been to research, prototype, and deploy computer visions systems that accelerate the capabilities of human rights researchers and investigative journalists.

More precisely, the VFRAME project develops two main technologies: a core image processing engine to analyze large collections of videos (millions) or images (billions), and a synthetic data rendering system to generate high-fidelity training data. Together, these two approaches are being utilized to develop accurate object detectors capable of locating objects of interest (e.g. an RBK-250 tailfin or a 9N235 submunition) in millions of video files culled from online sources.

Stay tuned for more updates during 2022 including the release of a new 9N235 detector and the final models for the RBK-250, RBK-500, and AO-25RT submunition.

Team

 Adam Harvey / DirectorWorking in Python on computer vision, image processing, 3D rendering, and systems engineering. Contact
Adam Harvey / Director
Working in Python on computer vision, image processing, 3D rendering, and systems engineering. Contact
 Jules LaPlace / CollaboratorWorking with Python, React, and MySQL on information architecture, image retrieval and interface design.
Jules LaPlace / Collaborator
Working with Python, React, and MySQL on information architecture, image retrieval and interface design.
 Josh Evans / CollaboratorWorking with Blender, photogrammetry and emerging 3D technologies.
Josh Evans / Collaborator
Working with Blender, photogrammetry and emerging 3D technologies.

Contact

For inquires about using VFRAME technologies please contact Adam Harvey on Keybase at keybase.io/vframeio (for tech support) or email [email protected] (a PGP key is available here).

Press Archive

Project Partners

Syrian Archive
VFRAME x T4T

Awards

Ars Electronica
Beazley Design of the Year Awards 2019
STARTS

Funding

Research and development of VFRAME is or has been supported by the ProtypeFund (DE), Swedish International Development Agency (SIDA), Meedan, and NL Net.

German Federal Ministry of Education and Research - BMBF
Meedan / Check Global
NLNet and NGI0
Prototype Fund

About this site

This site is designed to be privacy-friendly and does not use any 3rd party analytics to track visits, nor any 3rd party dependencies that compromise privacy or share data. The site is built with Markdown, generated in Python, and served as static files.