[Retracted] Deep Unsupervised Hashing for Large-Scale Cross-Modal Retrieval Using Knowledge Distillation Model

Table 3

The MAP@50 results of two retrieval tasks on NUS-WIDE with various code lengths.

Methods	Image-query-text				Text-query-image
	16	32	64	128	16	32	64	128
CVH [7]	0.372	0.362	0.406	0.390	0.401	0.384	0.442	0.432
IMH [11]	0.470	0.473	0.476	0.459	0.478	0.483	0.472	0.462
CMFH [24]	0.455	0.459	0.465	0.467	0.529	0.577	0.614	0.645
LSSH [26]	0.481	0.489	0.507	0.507	0.455	0.459	0.416	0.473
DBRC [31]	0.424	0.459	0.447	0.447	0.455	0.459	0.416	0.473
UDCMH [28]	0.511	0.519	0.524	0.558	0.637	0.653	0.695	0.716
DJSRH [29]	0.724	0.773	0.798	0.817	0.712	0.744	0.771	0.789
JDSH [27]	0.736	0.793	0.832	0.835	0.721	0.785	0.794	0.804
Ours	0.764	0.809	0.837	0.836	0.759	0.796	0.808	0.819