VGG16
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A to Z
- A · App
- No
- B · Built By
- University of Oxford
- C · CEO & Politics
- N/A (academic research) — No public partisan activity documented
- D · Date
- 2014
- E · Expertise
- Intermediate+
- F · Free Tier
- No free tier
- G · Generates
- Text only
- H · Deployment
- Cloud + Local (open weights)
- I · Inputs
- Text
- J · Jurisdiction
- UK
- K · Key Staffers
- Karen Simonyan (Lead author), Andrew Zisserman (Senior author)
- L · Languages
- English-primary
- M · Model Type
- Vision/CV
- N · Safety Issues
- Computer-vision risks: dataset bias, domain shift, privacy concerns in images, and unreliable performance outside benchmark-like settings.
- O · Open Source
- Yes — open weights
- P · Pricing
- Free (open weights, CC BY 4.0)
- Q · AIDb Rating
- 4/10 · AIDb v2.0 (rule-based): Capability 4/10 · Currency 4/10 · Access 5/10 · Significance 4/10 → 4.15
- R · What Makes It Special
- The University of Oxford Visual Geometry Group's VGG16, the 16-weight-layer network from Karen Simonyan and Andrew Zisserman's very deep convolutional networks study, which showed that stacking very small 3x3 convolution filters to a depth of 16 to 19 layers markedly beat earlier designs; it underpinned the team's ILSVRC-2014 entry, which took first place in localisation and second in classification, and its weights were released under a Creative Commons Attribution license.
- S · Stock / Status
- University
- T · Training Cutoff
- [UNKNOWN]
- U · Users
- [UNKNOWN]
- V · Voice Chat
- No
- W · Weights
- Downloadable
- X · X Handle
- [UNKNOWN]
- Y · Year Founded
- [UNKNOWN]
- Z · Bottom Line
- Open-weights Vision/CV from University of Oxford, released 2014.
Data completeness 85% · Last verified 2026-06-11 · Primary source ↗
Cite this
“VGG16.” AIDb — The AI Database. Verified 2026-06-11. https://theaidatabase.com/m/vgg16-university-of-oxford.html