# Multi-Label Weighted Contrastive Cross-Modal Hashing
## 4 Experiment
### Performance Comparisons and Discussion
\begin{table}
\begin{tabular}{l c c c c c c} \hline \hline  & \multicolumn{4}{c}{**MIRFLICKR-25K**} \\ \cline{2-7}
**Methods** & \multicolumn{2}{c}{**I2T**} & \multicolumn{4}{c}{**T2I**} \\ \cline{2-7}  & **16 Bits** & **32 Bits** & **64 Bits** & **16 Bits** & **32 Bits** & **64 Bits** \\ \hline CVH & 0.5981 & 0.5988 & 0.6190 & 0.6151 & 0.6263 & 0.6311 \\ CCA-ITQ & 0.7814 & 0.7939 & 0.8043 & 0.7509 & 0.7594 & 0.7708 \\ SCM & 0.6800 & 0.6903 & 0.6972 & 0.6853 & 0.6909 & 0.7433 \\ DCMH & 0.7911 & 0.8128 & 0.8288 & 0.8092 & 0.8355 & 0.8293 \\ SSAH & 0.8409 & 0.8607 & 0.8781 & 0.8081 & 0.8314 & 0.8413 \\ DCHUC & 0.8190 & 0.8236 & 0.8299 & 0.8177 & 0.8296 & 0.8417 \\ Bi_NCMH & 0.8521 & 0.8704 & 0.8895 & 0.8192 & 0.8464 & 0.8541 \\ MMACH & 0.8652 & 0.8808 & 0.8923 & 0.8112 & 0.8395 & 0.8672 \\ SCCGDH & 0.8817 & 0.8918 & 0.8926 & 0.8204 & 0.8562 & 0.8716 \\ MLWCH (Ours) & **0.9216** & **0.9310** & **0.9450** & **0.8912** & **0.8987** & **0.9102** \\ \hline \hline \end{tabular}
\end{table} 
Table 2: The MAP@50 results of our method and baselines varied with different hash code lengths on MIRFLICKR-25K. The best results are bold-font. \begin{table}
\begin{tabular}{l c c c c c c} \hline \hline  & \multicolumn{3}{c}{**MS COCO**} & & & \\ \cline{2-7}
**Methods** & \multicolumn{2}{c}{**I2T**} & & & & & \\ \cline{2-7}  & **16 Bits** & **32 Bits** & **64 Bits** & **16 Bits** & **32 Bits** & **64 Bits** \\ \hline CVH & 0.3611 & 0.3497 & 0.3587 & 0.4267 & 0.4340 & 0.4262 \\ CCA-ITQ & 0.3504 & 0.3931 & 0.4120 & 0.4006 & 0.4124 & 0.4106 \\ SCM & 0.3697 & 0.3803 & 0.4161 & 0.4296 & 0.4383 & 0.4614 \\ DCMH & 0.5549 & 0.6053 & 0.6085 & 0.5723 & 0.5916 & 0.5986 \\ SSAH & 0.6203 & 0.6231 & 0.6390 & 0.5839 & 0.6203 & 0.6323 \\ DCHUC & 0.6138 & 0.6454 & 0.6595 & 0.5608 & 0.5903 & 0.6284 \\ Bi\_NCMH & 0.6857 & 0.7174 & 0.7442 & 0.6454 & 0.6836 & 0.7229 \\ MMACH & 0.7013 & 0.7345 & 0.7564 & 0.6761 & 0.7058 & 0.7323 \\ SCCGDH & 0.7317 & 0.7772 & 0.8084 & 0.7741 & 0.7813 & 0.8315 \\ MLWCH (Ours) & **0.8072** & **0.8271** & **0.8579** & **0.8350** & **0.8614** & **0.8924** \\ \hline \hline \end{tabular}
\end{table} 
Table 4: The MAP@50 results of our method and baselines varied with different hash code lengths on MS COCO. The best results are bold-font. Figure 4: Precision-recall curves on MIRFLICKR-25K, NUS-WIDE, and MS COCO datasets. The code length is 16 bits. \begin{table}
\begin{tabular}{l c c c c c c} \hline \hline  & \multicolumn{3}{c}{**NUS-WIDE**} & & \\ \cline{2-7}
**Methods** & \multicolumn{2}{c}{**I2T**} & & & & \\ \cline{2-7}  & **16 Bits** & **32 Bits** & **64 Bits** & **16 Bits** & **32 Bits** & **64 Bits** \\ \hline CVH & 0.6202 & 0.6360 & 0.6358 & 0.6174 & 0.6265 & 0.6352 \\ CCA-ITQ & 0.5955 & 0.6823 & 0.7303 & 0.6523 & 0.6584 & 0.6745 \\ SCM & 0.6587 & 0.6913 & 0.7072 & 0.6556 & 0.6898 & 0.7015 \\ DCMH & 0.7076 & 0.7248 & 0.7272 & 0.6835 & 0.6982 & 0.7130 \\ SSAH & 0.7103 & 0.7240 & 0.7794 & 0.6894 & 0.6858 & 0.6869 \\ DCHUC & 0.7432 & 0.7626 & 0.7678 & 0.6816 & 0.6726 & 0.6968 \\ Bi\_NCMH & 0.7417 & 0.7593 & 0.7963 & 0.7120 & 0.7212 & 0.7303 \\ MMACH & 0.7426 & 0.7645 & 0.8054 & 0.7074 & 0.7135 & 0.7274 \\ SCCGDH & 0.8124 & 0.8372 & 0.8401 & 0.7669 & 0.7734 & 0.7722 \\ MLWCH (Ours) & **0.8459** & **0.8546** & **0.8765** & **0.7886** & **0.7965** & **0.7990** \\ \hline \hline \end{tabular}
\end{table} 
Table 3: The MAP@50 results of our method and baselines varied with different hash code lengths on NUS-WIDE. The best results are bold-font.