更改作者（去掉CVPR标识）
% \usepackage{
cvpr} % To produce the CAMERA-READY version
\usepackage[review]{
cvpr} % To produce the REVIEW version
改成
\usepackage{
cvpr} % To produce the CAMERA-READY version
% \usepackage[review]{
cvpr} % To produce the REVIEW version
插入图片
横屏单图
\begin{
figure*}
\centering
\includegraphics[width=\linewidth]{
fig/fig2.pdf}
% \begin{
subfigure}{
\linewidth}
\caption{
Overview of DCPNeRF. }
\label{
fig:2}
% \end{
subfigure}
\end{
figure*}
多子图
\begin{
figure}[!t]
\centering
\subfloat[Haz inputs]{
\label{
fig:fig1.a}
\includegraphics[scale=0.38]{
fig/fig1_a.png}}
\subfloat[Haz outputs]{
\label{
fig:fig1.b}
\includegraphics[scale=0.38]{
fig/fig1_b.png}}
\subfloat[Clear outputs]{
\label{
fig:fig1.c}
\includegraphics[scale=0.38]{
fig/fig1_c.png}}
\subfloat[Clear Depth]{
\label{
fig:fig1.d}
\includegraphics[scale=0.38]{
fig/fig1_d.png}}
\caption{
{
\bf Results of DCPNeRF.} Given a set of hazy images (a), DCPNeRF utilizes two neural radiance field components to jointly reconstruct the hazy scene (b). By combining DCP atmospheric light estimation and soft density-guided weights, a dehazed representation of the clear scene (c) is obtained from the hazy scene. Additionally, this method accurately estimates the depth map (d) of the clear scene.}
\label{
fig:1}
\end{
figure}
插入表格
普通表格
\begin{
table}
\centering
\begin{
tabular}{
ccc}
\toprule
Method & PSNR($\uparrow$) & SSIM($\uparrow$) \\
\midrule
w/o $\mathcal{
L}_{
foggy}$ & 24.70 & 0.91 \\
w/o $\mathcal{
W}^{
\alpha}$ & 24.90 & 0.93 \\
DCPNeRF & \textbf{
27.00} & \textbf{
0.94}\\
\bottomrule
\end{
tabular}
\caption{
{
\bf In the ablation experiment of $L_{
foggy}$ and $W^{
\alpha}$ in the Lego scene.} }
\label{
tab:2}
\end{
table}
三线表
\begin{
table}
\resizebox{
\linewidth}{
!}{
\begin{
tabular}{
c|cccccc}
\hline
& \multicolumn{
2}{
c}{
Lego} & \multicolumn{
2}{
c}{
Hotdog} & \multicolumn{
2}{
c}{
Chair} \\
Method & PSNR($\uparrow$) & \multicolumn{
1}{
c|}{
SSIM($\uparrow$)} & PSNR($\uparrow$) & \multicolumn{
1}{
c|}{
SSIM($\uparrow$)} & PSNR($\uparrow$) & SSIM($\uparrow$) \\ \hline
DCP+NGP & 23.90 & \multicolumn{
1}{
c|}{
\textbf{
0.95}} & 19.60 & \multicolumn{
1}{
c|}{
\st{
1.13} } & 23.30 & \st{
1.09} \\
\begin{
tabular}[c]{
@{
}c@{
}}WeatherDiffusion\\ +NGP\end{
tabular} & 20.30 & \multicolumn{
1}{
c|}{
\st{
1.37}} & 20.80 & \multicolumn{
1}{
c|}{
\st{
1.46}} & 22.10 & \st{
1.55} \\
FFANet+NGP & 22.50 & \multicolumn{
1}{
c|}{
0.92} & 23.30 & \multicolumn{
1}{
c|}{
0.93} & 21.90 & 0.94 \\ \hline
\textbf{
DCPNeRF} & \textbf{
27.00} & \multicolumn{
1}{
c|}{
0.94} & \textbf{
29.50} & \multicolumn{
1}{
c|}{
\textbf{
0.95}} & \textbf{
30.60} & \textbf{
0.97} \\ \hline
\end{
tabular}
}
\caption{
{
\bf Quantitative comparison using Lego synthetic data with heterogeneous haze.}}
\label{
tab:1}
\end{
table}
列表
无序列表
\begin{
itemize}
\item one
\item two
\item three
\end{
itemize}
有序列表
\begin{
enumerate}[(1)]
\item 有编号的列表
\item ...
\end{
enumerate}
注意：[(1)]可以变成[{[1]}], [(i)], …
正文注意点
插入url
\url{
https://www.baidu.com}
首段不缩进
\noindent
正文段落首句子体加粗加黑
{
\bf Image Dehazing.}
所有标题都要注意大写
公式中的字母在正文出现要和公式一样，也就是用斜体
$r(t) = o + td$
公式中出现的英文用要正体
{
\rm with}
公式解释where不缩进，公式结尾加逗号
引用公式、图片、表格等要统一
\Cref{
fig:fig6.c}
or
\cref{
fig:fig6.c}
参考文献
- 不要过于详细谷歌学术，当遇到arxiv时要仔细查找文献出处。
- 检查论文标题要与原文一致，注意大小写
- title加双括号，避免大小写编译错误
@inproceedings{
ancuti2012enhancing,
author={
Ancuti, Cosmin and Ancuti, Codruta Orniana and Haber, Tom and Bekaert, Philippe},
booktitle={
2012 IEEE Conference on Computer Vision and Pattern Recognition},
title={
{
Enhancing underwater images and videos by fusion}},
year={
2012},
pages={
81-88}
}