Evaluation Data (Semi-Supervised Image Classification)
ImageNet-1K
#Evaluation Metric-Acc@1, Acc@5
Data Description:
ImageNet-1K is a subset of the ImageNet dataset used for ILSVRC2012. It consists of 1000 classes with approximately 1.2 million images in the training set and 50,000 images in the validation set. 30,000 images are sampled from the original training set as the validation set, and the original validation set is used as the test set.
Dataset structure:
Amount of source data:
The dataset is divided into auxiliary training set (1,251,167), with 10% of the data labeled and the remaining 90% as unlabeled, validation set (30,000), and test set (50,000).
Amount of test data:
All 50,000 test examples from the original test set.
Data detail:
| KEYS | EXPLAIN |
|---|---|
| images | RGB images for input |
| labels | Class labels for each image |
Sample of source dataset:
RGB image：
label：
n01440764
Citation:
@inproceedings{deng2009imagenet,
title={Imagenet: A large-scale hierarchical image database},
author={Deng, Jia and Dong, Wei and Socher, Richard and Li, Li-Jia and Li, Kai and Fei-Fei, Li},
booktitle={Computer Vision and Pattern Recognition},
pages={248--255},
year={2009},
organization={IEEE}
}Place365 Standard
#Evaluation Metric-Acc@1, Acc@5
Data Description:
The Places365 Standard dataset is a scene recognition dataset with 1,800,000 images from 365 scene categories, including 36,500 validation images. 18,000 images are sampled from the original training set as the validation set, and the rest are used as the training set. The original validation set is used as the test set.
Dataset structure:
Amount of source data:
The dataset is divided into auxiliary training set (1,782,000), with 10% of the data labeled and the remaining 90% as unlabeled, validation set (18,000), and test set (36,500).
Amount of test data:
All 36,500 test examples from the original test set.
Data detail:
| KEYS | EXPLAIN |
|---|---|
| images | RGB images for input |
| labels | Class labels for each image |
Sample of source dataset:
RGB image：
label：
airfield
Citation:
@article{zhou2017places,
title={Places: A 10 million image database for scene recognition},
author={Zhou, Bolei and Lapedriza, Agata and Khosla, Aditya and Oliva, Aude and Torralba, Antonio},
journal={IEEE transactions on pattern analysis and machine intelligence},
volume={40},
number={6},
pages={1452--1464},
year={2017},
publisher={IEEE}
}