Computer Vision for OSINT Research

VFRAME develops and applies state-of-the-art computer vision technologies to human rights research and conflict zone monitoring.

September 2022: Scheduled release of 9N235/210 submunition detector

August 2022: VFRAME announces partnership with Tech 4 Tracing to gain access to munitions for scanning and benchmark datasets.

June 2022: Adam Harvey presents VFRAME's latest technology and research at the United Nations Eighth Biennial Meeting of States on Small Arms and Light Weapons in NYC

Below ⤵︎ Latest prototype for a publicly available 9N235/210 object detector

August 2022: VFRAME's latest 9N235/210 detector shown in high difficulty test. Munition is partially occluded by grass and partially occluded in ground. Tailfins and main tube show scattered dirt. Head mounted perspective. Recorded in direct sunlight. © Adam Harvey / VFRAME.io

Current Research and Prototypes

9N235/210 Object Detector
  • 9N235/210 Object Detector
  • Building the 9N235/210 object detector
3D Printed Training Data
  • 3D Printed Training Data
  • Enriching synthetic data with 3D printed cluster munition replicas for use in image training datasets
3D Rendered Training Data
  • 3D Rendered Training Data
  • Using 3D modeled scenes to build synthetic training datasets for objects in conflict zones
Cluster Munition Detector
  • Cluster Munition Detector
  • Training object detection algorithms to locate illegal munitions
Scene Summarization
  • Scene Summarization
  • Content-based scene summarization to find the most representative frames in videos

About VFRAME

Human rights researchers often rely on videos shared online to document war crimes, atrocities, and human rights violations. Manually reviewing these videos is expensive, does not scale, and can cause vicarious trauma. As an increasing number of videos are posted, a new approach is needed to understand these large datasets.

VFRAME has been working with Mnemonic.org, a Berlin-based organization dedicated to documenting war crimes and human rights violations, to develop computer vision tools to address these challenges.

Specifically, VFRAME has been developing a scalable computer vision system for large-scale analysis of video archives to detect illegal munitions, and redaction tools to blur faces. VFRAME can detect objects, such as the RBK-250 munition found in videos from the Syrian conflict, with up to 99% accuracy at over 400 FPS on a single desktop.

Read more about who we are and what we do.

Recent Press

Collaborations

Syrian Archive
VFRAME x T4T

Funding

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

Awards

Ars Electronica
Beazley Design of the Year Awards 2019
STARTS

DISCLAIMER

NEVER HANDLE OR APPROACH ANY MUNITION WITHOUT EXPLOSIVE ORDNANCE DISPOSAL (EOD) TRAINING OR SUPERVISION FROM EOD PERSONNEL.