ImageNet Large Scale Visual Recognition Challenge 2013 (ILSVRC2013)
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Olga Russakovsky*, Jia Deng*, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg and Li Fei-Fei. (* = equal contribution) ImageNet Large Scale Visual Recognition Challenge. arXiv:1409.0575, 2014.
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bibtex
Development Kit
- Overview and statistics of the data.
- Meta data for the competition categories.
- Matlab routines for evaluating submissions.
Please be sure to consult the included readme.txt file for competition details. Additionally, the development kit includes
Development kit (updated Aug 24, 2013)
DET dataset
There are a total of 395,909 images for training. The number of positive images for each synset (category) ranges from 417 to 66,911. The number of negative images ranges from 185 to 10,073 per synset. There are 20121 validation images, and 40,152 test images. All images are in JPEG format.
Training images. 40GB. MD5: 516b61e845794133b7e049d59f52a65a
- There is significant overlap between the CLS-LOC training images below (also used for the ILSVRC2012 challenge) and the DET training images.
Those who have already downloaded the CLS-LOC data can download just the new DET images here. Please carefully consult the readme.txt in the development kit
for the list of images which may be used for the detection challenge.
Training images not in CLS-LOC data. 14GB. MD5: b093799ab4d9be34662a83a58cd36919
Validation images. 2.6GB. MD5: 6309b18badce0e60cd541e78e47b2f40
Test images. 5.1GB. MD5: 87b253f544b02e959f7078be18d55660
CLS-LOC dataset
This dataset is unchanged from ILSVRC2012.
There are a total of 1,281,167 images for training. The number of images for each
synset (category) ranges from 732 to 1300. There are 50,000 validation images, with 50 images per synset.
There are 100,000 test images. All images are in JPEG format.
Terms of use: by downloading the image data from the above URLs, you agree to the following terms:
DET dataset
Training bounding box annotations . 11MB. MD5: 1d13d5461bff249ee96661253114314a
Validation bounding box annotations . 1.4MB. MD5: f620a26bee2d9f6655baa548d18a58ac
CLS-LOC dataset
Training bounding box annotations . 20MB. MD5: 9271167e2176350e65cfe4e546f14b17
Validation bounding box annotations . 2.2MB. MD5: f4cd18b5ea29fe6bbea62ec9c20d80f0