
% \begin{table*}[!ht]
%     \centering
%     \caption{Quantitative Comparison of Registration performance with GT in the hard-cases after initial rotation compensation on the axis with the largest rotation. cr denotes the compensation rotation angle. \textbf{Bold} and \underline{underline} highlights the best and second best performance among algorithm registration results. * highlight significant improvements (paired t-test, p\textless 0.05). The proposed LOTUS-based methods significantly decrease the rotation and translation error compared to the baselines.}
%     \begin{adjustbox}{width=\textwidth}
%     \setlength{\tabcolsep}{5pt}
%     \renewcommand{\arraystretch}{1}
%     \footnotesize % 使用小字体
%     \begin{tabular}{l|ccc|ccc}
%     \hline
%         \multirow{2}{*}{Metric} & \multicolumn{3}{c|}{$\lvert ER\rvert$ ↓} & \multicolumn{3}{c}{$\Vert ET\Vert$ ↓} \\ 
%         \cline{2-7}
%         & \multicolumn{1}{c|}{cr=10} & \multicolumn{1}{c|}{cr=20} & \multicolumn{1}{c|}{cr=30} & \multicolumn{1}{c|}{cr=10} & \multicolumn{1}{c|}{cr=20} & \multicolumn{1}{c}{cr=30} \\ 
%         \hline
%         ANTs & \multicolumn{1}{c|}{79.21$\pm$30.94} & \multicolumn{1}{c|}{69.17$\pm$32.83} & \multicolumn{1}{c|}{58.90$\pm$30.63} & \multicolumn{1}{c|}{49.80$\pm$19.46} & \multicolumn{1}{c|}{42.89$\pm$19.23} & \multicolumn{1}{c}{35.71$\pm$17.61} \\ 
%         Greedy & \multicolumn{1}{c|}{82.97$\pm$31.14} & \multicolumn{1}{c|}{74.00$\pm$39.33} & \multicolumn{1}{c|}{58.33$\pm$45.59} & \multicolumn{1}{c|}{52.59$\pm$19.85} & \multicolumn{1}{c|}{47.69$\pm$25.26} & \multicolumn{1}{c}{35.81$\pm$29.21} \\ 
%         % \hline
%         LOTUS(ANTs) & \multicolumn{1}{c|}{72.56$\pm$29.10} & \multicolumn{1}{c|}{55.80$\pm$34.40} & \multicolumn{1}{c|}{37.91$\pm$38.31} & \multicolumn{1}{c|}{47.52$\pm$19.49} & \multicolumn{1}{c|}{36.08$\pm$22.83} & \multicolumn{1}{c}{22.70$\pm$22.37} \\ 
%         LOTUS(Greedy) & \multicolumn{1}{c|}{\textbf{59.47$\pm$45.28}} & \multicolumn{1}{c|}{\textbf{48.98$\pm$43.18}} & \multicolumn{1}{c|}{\textbf{34.13$\pm$45.74}} & \multicolumn{1}{c|}{\textbf{36.58$\pm$28.29}} & \multicolumn{1}{c|}{\textbf{30.83$\pm$27.70}} & \multicolumn{1}{c}{\textbf{21.32$\pm$29.25}} \\ 
%         \hline
%     \end{tabular}
%     \end{adjustbox}
%     \label{tab:quant_results}
% \end{table*}


\begin{table*}[!ht]
    \centering
    \caption{Registration performance on hard cases, using the GT for evaluation. CR denotes the compensation rotation angle. \textbf{Best} and \underline{second}  performances are highlighted. LOTUS outpainting significantly decreases the rotation error (RE) and translation error (TE) (*, paired t-tests, p\textless 0.05) compared to the baselines.
    }
    \begin{adjustbox}{width=\textwidth}
    \setlength{\tabcolsep}{5pt}
    \renewcommand{\arraystretch}{1}
    \footnotesize % 
    \begin{tabular}{l|ccc|ccc}
    \hline
        \multirow{2}{*}{Metric} & \multicolumn{3}{c|}{RE ↓} & \multicolumn{3}{c}{TE ↓} \\ 
        \cline{2-7}
        & \multicolumn{1}{c|}{CR=10$^\circ$} & \multicolumn{1}{c|}{CR=20$^\circ$} & \multicolumn{1}{c|}{CR=30$^\circ$} & \multicolumn{1}{c|}{CR=10$^\circ$} & \multicolumn{1}{c|}{CR=20$^\circ$} & \multicolumn{1}{c}{CR=30$^\circ$} \\ 
        \hline
        ANTs & \multicolumn{1}{c|}{69.5$\pm$27.8} & \multicolumn{1}{c|}{57.7$\pm$26.84} & \multicolumn{1}{c|}{47.3$\pm$22.6} & \multicolumn{1}{c|}{44.7$\pm$18.5} & \multicolumn{1}{c|}{37.4$\pm$17.5} & \multicolumn{1}{c}{30.5$\pm$14.7} \\ 
        Greedy & \multicolumn{1}{c|}{73.7$\pm$28.8} & \multicolumn{1}{c|}{62.4$\pm$36.7} & \multicolumn{1}{c|}{44.6$\pm$41.7} & \multicolumn{1}{c|}{47.9$\pm$19.4} & \multicolumn{1}{c|}{41.8$\pm$25.2} & \multicolumn{1}{c}{29.2$\pm$28.2} \\ 
         \hline
        LOTUS(ANTs) & \multicolumn{1}{c|}{\underline{63.7$\pm$25.0}} & \multicolumn{1}{c|}{\underline{43.8$\pm$27.6}} & \multicolumn{1}{c|}{\underline{21.5$\pm$21.9}} & \multicolumn{1}{c|}{\underline{41.1$\pm$16.1}} & \multicolumn{1}{c|}{\underline{28.2$\pm$18.5}} & \multicolumn{1}{c}{\underline{13.9$\pm$14.0}} \\ 
        LOTUS(Greedy) & \multicolumn{1}{c|}{\textbf{44.7$\pm$39.4}} & \multicolumn{1}{c|}{\textbf{33.7$\pm$34.5}} & \multicolumn{1}{c|}{\textbf{8.35$\pm$28.68}} & \multicolumn{1}{c|}{\textbf{28.4$\pm$25.7}} & \multicolumn{1}{c|}{\textbf{22.2$\pm$23.4}} & \multicolumn{1}{c}{\textbf{5.57$\pm$20.52}} \\ 
        \hline
    \end{tabular}
    \end{adjustbox}
    \label{tab:appendix:quant_results}
\end{table*}