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Found 5 papers, 3 papers with code
One Noise to Rule Them All: Learning a Unified Model of Spatially-Varying Noise Patterns
Procedural noise is a fundamental component of computer graphics pipelines, offering a flexible way to generate textures that exhibit "natural" random variation.
Explorable Mesh Deformation Subspaces from Unstructured Generative Models
Deep generative models of 3D shapes often feature continuous latent spaces that can, in principle, be used to explore potential variations starting from a set of input shapes.
Learning Transferable 3D Adversarial Cloaks for Deep Trained Detectors
This paper presents a novel patch-based adversarial attack pipeline that trains adversarial patches on 3D human meshes.
Playing Chess with Limited Look Ahead
We have seen numerous machine learning methods tackle the game of chess over the years.
Triangle Inscribed-Triangle Picking
Given a triangle ABC, we derive the probability distribution function and the moments of the area of an inscribed triangle RST whose vertices are uniformly distributed on AB, BC, and CA.
General Mathematics 60D05
