LookingGlass：基于拉普拉斯金字塔形变生成的错视艺术

LookingGlass: Generative Anamorphoses via Laplacian Pyramid Warping

April 11, 2025

作者: Pascal Chang, Sergio Sancho, Jingwei Tang, Markus Gross, Vinicius C. Azevedo

cs.AI

摘要

变形图像（Anamorphosis）是指一类经过刻意扭曲处理的图像，直接观看时难以辨认其真实形态。只有当通过特定视角，如借助反射镜或透镜等折反射装置观察时，其原本面貌才得以显现。尽管这类数学装置的构建可追溯至17世纪，但它们仅在特定观察点下可被解读，常规视角下则往往失去意义。本文以生成式视角重新审视这些著名的视觉错觉现象。借助潜在校正流模型，我们提出了一种方法，能够创建即便直接观看仍保持有效解读的变形图像。为此，我们引入了拉普拉斯金字塔变形技术，这是一种频率感知的图像变形方法，对生成高质量视觉效果至关重要。我们的工作将视觉字谜（Visual Anagrams，arXiv:2311.17919）扩展至潜在空间模型及更广泛的空间变换，从而开创了新型生成式感知错觉的创作可能。

English

Anamorphosis refers to a category of images that are intentionally distorted, making them unrecognizable when viewed directly. Their true form only reveals itself when seen from a specific viewpoint, which can be through some catadioptric device like a mirror or a lens. While the construction of these mathematical devices can be traced back to as early as the 17th century, they are only interpretable when viewed from a specific vantage point and tend to lose meaning when seen normally. In this paper, we revisit these famous optical illusions with a generative twist. With the help of latent rectified flow models, we propose a method to create anamorphic images that still retain a valid interpretation when viewed directly. To this end, we introduce Laplacian Pyramid Warping, a frequency-aware image warping technique key to generating high-quality visuals. Our work extends Visual Anagrams (arXiv:2311.17919) to latent space models and to a wider range of spatial transforms, enabling the creation of novel generative perceptual illusions.