论文标题
带有各种自动编码器的嵌入和生成室内攀爬路线
Embedding and generation of indoor climbing routes with variational autoencoder
论文作者
论文摘要
室内攀岩的最新流行度增加，可以使深度学习算法的应用可以对攀岩路线进行分类和生成攀岩路线。在这项工作中，我们在标准化的培训设备月板上使用跨自动编码器来攀爬路线，这是攀岩社区中众所周知的培训工具。通过对编码的潜在空间进行采样，可以观察到该算法可以生成高质量的攀岩路线。 22个生成的问题上传到月板应用程序以供用户审核。该算法可以作为促进室内攀爬路线设置的第一步。
Recent increase in popularity of indoor climbing allows possible applications of deep learning algorthms to classify and generate climbing routes. In this work, we employ a variational autoencoder to climbing routes in a standardized training apparatus MoonBoard, a well-known training tool within the climbing community. By sampling the encoded latent space, it is observed that the algorithm can generate high quality climbing routes. 22 generated problems are uploaded to the Moonboard app for user review. This algorithm could serve as a first step to facilitate indoor climbing route setting.
