论文标题
计算机图形中的代码可复制性
Code Replicability in Computer Graphics
论文作者
论文摘要
能够复制已发表的研究结果是进行研究是基于这些发现还是与之比较的重要过程。当使用原始作者的工件（例如代码）或“可重复性”（例如，重新实现算法）时，此过程称为“复制性”。最近，通过在各个领域进行评估研究的研究结果，可重复性和研究结果的可复制性引起了很多兴趣，并且通常被视为触发更好的结果扩散和透明度的触发因素。在这项工作中，我们通过评估代码是否可用以及是否正常工作来评估计算机图形的可复制性。作为该领域的代理，我们汇编，运行并分析了2014年，2016年和2018年Siggraph会议的374篇论文中的151个代码。该分析表明，具有可用和操作研究代码的论文数量有明显的增加，并依赖于子场，并指示代码可复制性和引文数量之间的相关性。我们进一步提供了一个交互式工具来探索我们的结果和评估数据。
Being able to duplicate published research results is an important process of conducting research whether to build upon these findings or to compare with them. This process is called "replicability" when using the original authors' artifacts (e.g., code), or "reproducibility" otherwise (e.g., re-implementing algorithms). Reproducibility and replicability of research results have gained a lot of interest recently with assessment studies being led in various fields, and they are often seen as a trigger for better result diffusion and transparency. In this work, we assess replicability in Computer Graphics, by evaluating whether the code is available and whether it works properly. As a proxy for this field we compiled, ran and analyzed 151 codes out of 374 papers from 2014, 2016 and 2018 SIGGRAPH conferences. This analysis shows a clear increase in the number of papers with available and operational research codes with a dependency on the subfields, and indicates a correlation between code replicability and citation count. We further provide an interactive tool to explore our results and evaluation data.
