我必须将这个表格放入一页。使用adjustcode失败，因为它使标题粘在表格的第一个单元格上，而不是跨越表格顶部。
该论文是双栏式的，因此我使用\begin{table*}而不是\begin{table}将表格填充为两栏。
\processtable用作表格的标题。
\botrule和\midrule是\toprule画线命令。
当前输出如下所示： https://i.stack.imgur.com/TJ4ln.jpg
\documentclass{cta-author}
.
.
.
\begin{table*}[ht]
\processtable{Some of the works with their contributions to the field and their recognition rates\label{tbl:0}}
{\begin{tabular*}{20pc}{@{\extracolsep{\fill}}lll@{}}\toprule
Method & Contribution & Recognition Rate \\
\midrule
Lopes et. al. & Generating synthetic samples to broaden the database for CNN learning process & 98.92 \\
BDBN & A set of weak classifiers that each is responsible for classifying one expression. & 96.70 \\
AUDP & Decomposing a facial expression into Micro-Action-Patterns and grouping them for higher level representation & 93.70 \\
Fan \& Tjahjadi & spatial–temporal framework based on histogram of gradients and optical flow & 83.70 \\
Zhong et. al. & two-stage multi-task sparse learning (MTSL) framework to efficiently locate the discriminative patches that discloses the expressions & 93.30 \\
Liu et. al. & manifold modeling of videos based on a proposed mid-level representation, i.e. expressionlet & 94.19 \\
Gu et. al. & A radial encoding strategy for efficiently downsampling Gabor filter outputs and a new classifier combination method by extracting information from local classifiers. & 91.51 \\
Proposed & asdsa & 99 \\
\botrule
\end{tabular*}}{}
\end{table*}
答案1
假设您正在使用 David 在评论中指出的文档类，您可以使用以下方法解决您的问题tabularx：
\documentclass{cta-author}
\usepackage{tabularx}
\begin{document}
\begin{table*}[ht]
\processtable{Some of the works with their contributions to the field and their recognition rates\label{tbl:0}}
{\begin{tabularx}{\textwidth}{@{}lXl@{}}\toprule
Method & Contribution & Recognition Rate \\
\midrule
Lopes et. al. & Generating synthetic samples to broaden the database for CNN learning process & 98.92 \\
BDBN & A set of weak classifiers that each is responsible for classifying one expression. & 96.70 \\
AUDP & Decomposing a facial expression into Micro-Action-Patterns and grouping them for higher level representation & 93.70 \\
Fan \& Tjahjadi & spatial–temporal framework based on histogram of gradients and optical flow & 83.70 \\
Zhong et. al. & two-stage multi-task sparse learning (MTSL) framework to efficiently locate the discriminative patches that discloses the expressions & 93.30 \\
Liu et. al. & manifold modeling of videos based on a proposed mid-level representation, i.e. expressionlet & 94.19 \\
Gu et. al. & A radial encoding strategy for efficiently downsampling Gabor filter outputs and a new classifier combination method by extracting information from local classifiers. & 91.51 \\
Proposed & asdsa & 99 \\
\botrule
\end{tabularx}}{}
\end{table*}
\end{document}
