深度学习——图像分类与检测领域常用数据集汇总

图像分类与检测领域常用数据集汇总

 图像分类与检测领域常用数据集

数据库	图像数目	类别数目	每类图像数目	图像大小（pixel）	数据库论文（点击即可获取论文，如果无法下载，推荐使用SCI-HUB）
MNIST	60000	10	6000	28x28	Gradient-based learning applied to document recognition
CIFAR-10	60000	10	6000	32x32	Learning multiple layers of features from tiny images
MPEG-7	1400	70	20	256x256-650x600	Shape descriptors for non-rigid shapes with a single closed contour
15 Scenes	4485	15	200-400	约 300x250	Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories
Caltech-101	9146	101	40-800	约 300x200	Learning generative visual models from few training examples: An incremental bayesian approach tested on 101 object categories
Caltech-256	30607	256	>80	约 300x200	Caltech-256 object category dataset
PASCAL VOC 2007	9963	20	96-2008	约 470x380	The PASCAL Visual Object Classes (VOC) Challenge
SUN397	108754	397	>100	约 500x300	Sun database: Large-scale scene recognition from abbey to zoo
SUN2012	16873	8	2000	约 500x300	Sun database: Large-scale scene recognition from abbey to zoo
Tiny Images	7900万	75062	-	32x32	80 million tiny images: A large data set for nonparametric object and scene recognition
ImageNet-1000	120万	1000	-	约 500x400	Imagenet: A large-scale hierarchical image database
ImageNet	1400万	10万	1000	约 500x400	Imagenet: A large-scale hierarchical image database

参考文献：黄凯奇, 任伟强, 谭铁牛. 图像物体分类与检测算法综述[J]. 计算机学报, 2014, 37(6): 1225-1240.