The ImageNet dataset contains 14,197,122 annotated images according to the WordNet hierarchy. Since 2010 the dataset is used in the ImageNet Large Scale Visual Recognition Challenge (ILSVRC), a benchmark in image classification and object detection.
The publicly released dataset contains a set of manually annotated training images. A set of test images is also released, with the manual annotations withheld.
ILSVRC annotations fall into one of two categories: (1) image-level annotation of a binary label for the presence or absence of an object class in the image, e.g., “there are cars in this image” but “there are no tigers,” and (2) object-level annotation of a tight bounding box and class label around an object instance in the image, e.g., “there is a screwdriver centered at position (20,25) with width of 50 pixels and height of 30 pixels”.
The ImageNet project does not own the copyright of the images, therefore only thumbnails and URLs of images are provided.
Source: ImageNet Large Scale Visual Recognition Challenge
Image Source: https://cs.stanford.edu/people/karpathy/cnnembed/
Variants: imagenet-1k, ImageNet sigma50, ImageNet sigma250, ImageNet sigma200, ImageNet sigma150, ImageNet sigma100, ImageNet100, ImageNet (linear), ImageNet (finetuned), ImageNet - 5-shot, ImageNet - 5 labeled data per class, ImageNet - 2 labeled data per class, ImageNet - 1-shot, ImageNet - 1 labeled data per class, ImageNet - 10-shot, ImageNet - 0.2% labeled data, ImageNetV2, ImageNet V2, ImageNet - 10% labeled data, ImageNet - 1% labeled data, ImageNet - 0-Shot, ImageNet
This dataset is used in 24 benchmarks:
Recent papers with results on this dataset: