Applied Informatics

Table 1 MAP scores of our RCN and compared methods

From: Cross-media residual correlation learning

Dataset	Method	Task
Dataset	Method	Image\(\rightarrow\)Text	Text\(\rightarrow\)Image	Average
Wikipedia dataset	CCA	0.176	0.178	0.177
	CFA	0.330	0.306	0.318
	KCCA (Poly)	0.230	0.224	0.227
	KCCA (Gaussian)	0.357	0.328	0.343
	Bimodal AE	0.301	0.267	0.284
	Multimodal DBN	0.204	0.145	0.175
	Corr-AE	0.373	0.357	0.365
	JRL	0.408	0.353	0.381
	LGCFL	0.416	0.360	0.388
	CMDN	0.409	0.364	0.387
	Deep-SM	0.458	0.345	0.402
	RCN (OnlyCorrelation)	0.465	0.407	0.436
	Our RCN	0.489	0.418	0.454
NUS-WIDE-10k dataset	CCA	0.159	0.189	0.174
	CFA	0.299	0.301	0.300
	KCCA (Poly)	0.129	0.157	0.143
	KCCA (Gaussian)	0.295	0.162	0.229
	Bimodal AE	0.234	0.376	0.305
	Multimodal DBN	0.178	0.144	0.161
	Corr-AE	0.306	0.340	0.323
	JRL	0.410	0.444	0.427
	LGCFL	0.408	0.374	0.391
	CMDN	0.410	0.450	0.430
	Deep-SM	0.389	0.496	0.443
	RCN (OnlyCorrelation)	0.360	0.406	0.383
	Our RCN	0.497	0.517	0.507
Pascal Sentences dataset	CCA	0.110	0.116	0.113
	CFA	0.341	0.308	0.325
	KCCA (Poly)	0.271	0.280	0.276
	KCCA (Gaussian)	0.312	0.329	0.321
	Bimodal AE	0.404	0.447	0.426
	Multimodal DBN	0.438	0.363	0.401
	Corr-AE	0.411	0.475	0.443
	JRL	0.416	0.377	0.397
	LGCFL	0.381	0.435	0.408
	CMDN	0.458	0.444	0.451
	Deep-SM	0.440	0.414	0.427
	RCN (OnlyCorrelation)	0.433	0.443	0.438
	Our RCN	0.472	0.453	0.463

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