关于LaTex下插入的图片排列问题及图片与文本排列问题

\begin{figure*}[tb]
	\centering
	\setlength{\abovecaptionskip}{0pt}
	\setlength{\belowcaptionskip}{0pt}
	\subfigure[show Fig.1]{\label{subfig:Fig.1}
		\begin{minipage}[t]{0.4\linewidth}
			\centering
			\vspace{0pt}
			\includegraphics[width=1.3\textwidth]{Fig1.eps}
		\end{minipage}
	}
	\quad
	\subfigure[show Fig.2]{\label{subfig: Fig.2}
		\begin{minipage}[t]{0.4\linewidth}
			\centering
			\vspace{0pt}
			\includegraphics[width=1.3\textwidth]{Fig2.eps}
		\end{minipage}
	}
	\quad
	\subfigure[show Fig.3]{\label{subfig:Fig.3}
		\begin{minipage}[t]{0.4\linewidth}
			\centering
			\vspace{0pt}
			\includegraphics[width=1.3\textwidth]{Fig2.eps}
		\end{minipage}
	}
	\captionsetup{font={footnotesize}}
	\caption{show three Figures.}
	\label{fig:all-Figure}
\end{figure*}

上述代码表示插入三张子图片，通过调整如下代码中的

\begin{minipage}[t]{0.4\linewidth}
			\centering
			\vspace{0pt}
			\includegraphics[width=1.3\textwidth]{Fig2.eps}
		\end{minipage}

0.4\linewidth及width=1.3\textwidth可以实现多种排列，如下图所示：

还可以在最上贴出的代码插入如下代码，在空白处添加文字：

\subfigure{\label{subfig: Thousand-FT-Probability}
	\begin{minipage}[t]{0.5\linewidth}
		\vspace{12pt}
We propose a novel deep network architecture that fuses
first order and second order information. We first extend the
bilinear network to combine first order information into the
learning process by designing a leaking shortcut which enables
the first order statistics to pass through and combine
with bilinear features. Our architecture enables more effective
learning by end-to-end training compared to the original
deep bilinear model.
	\end{minipage}
}

在上述代码中

\begin{figure*}[tb]

的*号表示跨栏排列，比如双栏模板，单栏模板的话就没啥影响。

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