Meschers are a new mesh representation for impossible geometric objects grounded in discrete exterior calculus that supports full discrete geometry processing including inverse rendering.
B., Berseth G., van de Panne M
4 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 4representative citing papers
A hybrid neural policy operating in impulse space enables physics-based characters to track exaggerated, dynamically infeasible motions that standard DRL methods cannot stabilize.
Method for generating minimum-weight structurally robust shell objects from 3D models using Laplacian parametrization to ensure intersection-free inner boundaries during stress-based thickness optimization.
Generative model with normalized pairwise distance constraint discovers output space topologies from sparse data and outperforms GANs and VAEs by avoiding mode collapse.
citing papers explorer
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Meschers: Geometry Processing of Impossible Objects
Meschers are a new mesh representation for impossible geometric objects grounded in discrete exterior calculus that supports full discrete geometry processing including inverse rendering.
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Neural Assistive Impulses: Synthesizing Exaggerated Motions for Physics-based Characters
A hybrid neural policy operating in impulse space enables physics-based characters to track exaggerated, dynamically infeasible motions that standard DRL methods cannot stabilize.
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Structural Design Using Laplacian Shells
Method for generating minimum-weight structurally robust shell objects from 3D models using Laplacian parametrization to ensure intersection-free inner boundaries during stress-based thickness optimization.
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Neural Embedding for Physical Manipulations
Generative model with normalized pairwise distance constraint discovers output space topologies from sparse data and outperforms GANs and VAEs by avoiding mode collapse.