Neural Foundations · 2009
ImageNet: A Large-Scale Hierarchical Image Database
Built a labelled image database of unprecedented scale and hierarchical structure, giving computer vision the large supervised benchmark it needed and creating the competition that deep learning went on to win.
Editorial record
Plain-language summary
ImageNet organised millions of human-labelled images into thousands of categories following the WordNet hierarchy, assembled through large-scale crowdsourcing. It supplied the data and the annual ILSVRC challenge that made it possible to train and fairly compare very large vision models. AlexNets 2012 win on this benchmark is widely taken as the moment deep learning became the dominant approach in vision.
Knowledge graph
Relationships
Antecedents
EnablesEvidence: Direct
AlexNet: ImageNet Classification with Deep CNNs
AlexNet was trained and evaluated on the ImageNet dataset and challenge
AlexNet 2012
EnablesEvidence: Strongly supported
CLIP: Learning Transferable Visual Models from NL Supervision
Large labelled image corpora underpin later vision-language pretraining
CLIP
Source record
Provenance
- Record ID
- A-040
- Record created
- 2026-07-13
- Last reviewed
- 2026-07-14
- Record version
- 2
Citation caveat: Citation metadata is approximate and marked unverified in the source dataset.