Basic Info

	A	B	C	D	E	F	G	H	I	J	K	L
1	No.	Dataset	# of Samples	# of Classes	# of Views	Feature Dim	Reference	File name	Official URL	Mark	Formated	Open Access
2	1	100Leaves	1,600	100	3	Shape(64)/Texture(64)/Margin(64)	Plant leaf classification using probabilistic integration of shape, texture and margin features	100Leaves.mat	One-hundred plant species leaves data set - UCI Machine Learning Repository		✅	✅
3	2	Deep AWA_2views	10,158	50	2	DECAF(4096)/VGG19(4096)	Deep Partial Multi-View Learning	AWA_Deep_2view.mat		a subset of AWA-7view-10158sample.mat	✅	✅
4	3	Reuters_2views	18,758	6	2	English(10)/French(10)	Multi-view Spectral Clustering Network	Reuters_dim10_2view.mat			✅	✅
5	4	Caltech101	9,144	102	6	Gabor(48)/Wavelet Moments(40)/CENTRIST(254)/HOG(1984)/GIST(512)/LBP(928)	Binary Multi-View Clustering	Caltech101.mat	Caltech 256 Image Dataset \| Kaggle		✅	✅
6	5	Caltech101-20	2,386	20			Deep Incomplete Multi-View Learning Network with Insufficient Label Information	Caltech101-20.mat			✅	✅
7	6	Caltech101-7	1,474	7			Large-scale multi-view spectral clustering via bipartite graph	Caltech101-7.mat			✅	✅
8	7	Deep Caltech101	8,677	101	2	DECAF(4096)/VGG19(4096)	TRUSTED MULTI-VIEW CLASSIFICATION	2view-caltech101-8677sample.mat			✅	✅
9	8	Caltech256	30,607	257	3	(1024)/(512)/(2048)	Auto-weighted Multi-view Clustering for Large-scale Data	Caltech256_fea.mat
10	9	NoisyMNIST	70,000	10	2	MNIST image(784)/Noise added MNIST image(784)	Robust Multi-View Clustering With Incomplete Information	NoisyMNIST.mat			✅	✅
11	10	NoisyMNIST-30000	30,000			MNIST image(784)/Noise added MNIST image(784)		NoisyMNIST-30000.mat			✅	✅
12	11	MNIST-USPS	5,000			MNIST image(784)/USPS image(256)		MNIST_USPS.mat			✅	✅
13	12	Scene15	4,485	15	3	GIST(20)/PHOG(59)/LBP(40)	Ensemble projection for semi-supervised image classification	Scene15.mat			✅	✅
14	13	Out-Scene	2,688	8	4	Color(432)/GIST(512)/HOG(256)/LBP(48)	Deep Incomplete Multi-View Learning Network with Insufficient Label Information	OutScene.mat			✅	✅
15	14	NUS-WIDE	30,000	31	5	CH(64)/CM(225)/CORR(144)/EDH(73)/WT(128)	Fast Multi-view Clustering via Ensembles: Towards Scalability, Superiority, and Simplicity	NUSWIDE.mat			✅	✅
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