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This paper introduces AutoMIA, an automated design pipeline for creating Mirror Illusion Art that generates a 3D object capable of displaying two distinct appearances based on reflection. The method addresses limitations of previous approaches by jointly optimizing shape and color while incorporating mechanisms to stabilize the optimization process and reduce artifacts. Key results show that AutoMIA can produce diverse and smooth artworks efficiently, with a design time of approximately 76 seconds and minimal memory usage on standard hardware.
AutoMIA can generate complex 3D illusions in under 80 seconds, revolutionizing the intersection of art and computational design.
Mirror Illusion Art is a novel reflection-conditioned 3D illusion where one object yields two target appearances (front and mirror). The task is formulated as inverse design from two target 2D images (front and mirror) to a printable 3D object with geometry and texture. Prior topology-driven and shadow-based approaches demand substantial manual effort, optimize shape only, and often yield non-smooth or incomplete geometry. To address these challenges, we propose AutoMIA, an automated Mirror Illusion Art design pipeline that jointly optimizes shape and color. To stabilize optimization and suppress artifacts, four mechanisms are introduced: (1) projection-alignment component (PAC) selection to reduce surface noise, (2) position-weighted adaptive (PWA) suppression for background noise, (3) internal voxel preservation (IVP) to prevent internal fractures, and (4) shape-color decoupled (SCD) optimization that balance shape and color optimization. AutoMIA generate diverse smooth Mirror Illusion artworks successfully both in the digital and physical world, with only around 76s design time and 2.6 GB memory on average using a single RTX 3090, advancing inverse graphics and computational design. Our code is available at https://github.com/zxp555/AutoMIA.
Tsinghua AI