Skip to content

CAP6412-Group-4/mdm-2-ddgan-report

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

66 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

MDM2DDGAN Report

LaTeX project for the final report.

Requirements

Make sure VS Code is installed: https://code.visualstudio.com

Installation

Install the LaTeX Workshop vscode extension by James Yu.

Install texlive:

sudo apt install texlive -y
sudo apt install latexmk -y

Add texlive to PATH:

export PATH=$PATH:/usr/local/texlive/2023/bin/x86_64-linux

CVPR 2023 Template

This is the LaTeX template for IEEE/CVF CVPR 2023 submissions, rebuttals, and final versions.

The last version of the CVPR/ICCV LaTeX template had been developed by [email protected] and [email protected] about 15 years ago. That version suffered from several issues:

  • Authors needed several individual files: cvpr.sty, cvpr_eso.sty, eso-pic.sty.
  • For CVPR/ICCV rebuttals, another version of cvpr.sty was required.
  • Several warnings arose due to deprecated options.

To address this, a new package was subsequently developed by Ming-Ming Cheng ([email protected]), which is intended to be used as a single style file that allows to build review, rebuttal, and final versions with just one package.

It is has been further modified by Stefan Roth ([email protected]) for CVPR 2022.

To apply it, simply use one of the following commands:

\documentclass[10pt,twocolumn,letterpaper]{article}

\usepackage[review]{cvpr}      % To produce the REVIEW version
%\usepackage[rebuttal]{cvpr}    % To produce a REBUTTAL
%\usepackage{cvpr}              % To produce the CAMERA-READY version

\def\cvprPaperID{*****} % *** Enter the CVPR Paper ID here
\def\confName{CVPR}
\def\confYear{2023}

Acknowledgements

This template is modified from the template by Ming-Ming Cheng from Nankai University ([email protected], see also https://github.com/MCG-NKU/CVPR_Template). That version was again modified from the the old CVPR/ICCV template files contributed by [email protected] and [email protected].

About

Report on improving efficiency of MDM model using a DDGAN

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Contributors 3

  •  
  •  
  •  

Languages