Neural Shadow Art
Caoliwen Wang, Bailin Deng, Juyong Zhang

TL;DR
Neural Shadow Art introduces an implicit occupancy function-based method to design high-resolution, topologically complex shadow sculptures that match arbitrary images from various angles, surpassing previous voxel- and mesh-based approaches.
Contribution
It presents a novel flexible framework using implicit functions for shadow art, enabling accurate projections of complex geometries under diverse lighting and orientation conditions.
Findings
Enhanced projection accuracy for complex geometries
Supports arbitrary topologies at any resolution
Reduces material usage and promotes surface smoothness
Abstract
Shadow art is a captivating form of sculptural expression where the projection of a sculpture in a specific direction reveals a desired shape with high precision. In this work, we introduce Neural Shadow Art, which leverages implicit occupancy function representation to significantly expand the possibilities of shadow art. This representation enables the design of high-quality, 3D-printable geometric models with arbitrary topologies at any resolution, surpassing previous voxel- and mesh-based methods. Our method provides a more flexible framework, enabling projections to match input binary images under various light directions and screen orientations, without requiring light sources to be perpendicular to the screens. Furthermore, we allow rigid transformations of the projected geometries relative to the input binary images and simultaneously optimize light directions and screen…
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Taxonomy
TopicsArt Therapy and Mental Health · Spatial Neglect and Hemispheric Dysfunction
