
ImageNet is an image database organized according to the WordNet hierarchy, featuring over 14 million images across 21,841 synsets. It serves as a crucial resource for advancing computer vision and deep learning research, providing free access to researchers for non-commercial use. The project has significantly contributed to the field by offering a vast collection of images that enhance the understanding and development of machine learning algorithms. Its scale and comprehensive organization make it a valuable tool for educators, students, and researchers alike, positioning it as a leader in the domain of image databases.

ImageNet is an image database organized according to the WordNet hierarchy, featuring over 14 million images across 21,841 synsets. It serves as a crucial resource for advancing computer vision and deep learning research, providing free access to researchers for non-commercial use. The project has significantly contributed to the field by offering a vast collection of images that enhance the understanding and development of machine learning algorithms. Its scale and comprehensive organization make it a valuable tool for educators, students, and researchers alike, positioning it as a leader in the domain of image databases.
Dataset scale: ~14.2M images across 21,841 WordNet synsets
Project type: Academic research dataset led by Prof. Li Fei-Fei and a senior research team
Construction method: Built (2009) by web image search plus crowdsourced verification via Amazon Mechanical Turk
Use & access: Data available for non-commercial research and education; ImageNet does not claim copyright on underlying images
Support: Project lists sponsors/supporters including Google, NVIDIA, NSF, A9, Princeton University, Stanford University
Computer vision / large-scale image classification and object recognition datasets
2009
Academic research / Computer vision dataset
“Project website lists sponsors/supporters (Google, NVIDIA, NSF, A9, Princeton University, Stanford University) rather than equity investors or public fundraising rounds.”