Constrained Injective Mapping Benchmark

<p>We are glad to&nbsp;release the benchmark dataset&nbsp;in our Siggraph Asia 2021&nbsp;paper&nbsp;<a href="https://duxingyi-charles.github.io/publication/optimizing-global-injectivity-for-constrained-parameterization/">Optimizing Global Injectivity for Constrained Parameterization</a>.&nbsp;The dataset is used to test various methods on their ability to recover an injective mapping from a non-injective initial mapping while keeping a group of positional constraints in place. The dataset&nbsp;includes <em>1791 </em>triangle mesh examples. Each example consists of an input rest mesh, an initial mesh, several constrained vertices (called handles), and&nbsp;a ground truth injective mapping obtained from the&nbsp;<a href="https://zenodo.org/record/3827969#.YVsE55qZOPp">Locally Injective Mappings Benchmark</a>.</p> <p>For reference, we also share our method&#39;s results on the examples in Constrained-Injective-Mappings-Result.zip.</p> <p>We hope that our dataset&nbsp;offers a benchmark for future research in this area.</p>