Surreal AI: The Generation, Reconstruction, and Assessment of Surreal Images and 3D Models

Surrealism applies metaphors to create a vocabulary of contexts and scenes. Can AI interpret surrealism? What occurs if a negative prompt is input for 3D reconstruction? This study aims to generate surreal images in AI and to assess the subsequent 3D reconstructed models as an exemplification of context. This AI interpretation study uses 87 sets of conflicting prompts to generate images with novel 3D structural and visual details. Eight characteristic 3D models were selected with geometric features modified by functions, such as the reduction in noise, to identify the changes made to the original shape, with upper and lower bounds of between 92.11% and 47.89% for area and between 20.51% and 1.46% for volume, which indicates structural details. This study creates a unique numeric identity of surreal images upon 3D reconstruction in terms of the relative % of the changes made to the original shape. AI can create a connection between 2D surreal imagination and the 3D physical world, in which the images and models are also appropriate for video morphing, situated elaboration in AR scenes, and verified 3D RP prints.