4 papers
Marching Neurons: Accurate Surface Extraction for Neural Implicit Shapes
Christian Stippel, Felix Mujkanovic, Thomas Leimkühler +1
Accurate surface geometry representation is crucial in 3D visual computing. Explicit representations, such as polygonal meshes, and implicit representations, like signed distance f…
Learning Neural Antiderivatives
Fizza Rubab, Ntumba Elie Nsampi, Martin Balint +4
Neural fields offer continuous, learnable representations that extend beyond traditional discrete formats in visual computing. We study the problem of learning neural representatio…
Learning Image Fractals Using Chaotic Differentiable Point Splatting
Adarsh Djeacoumar, Felix Mujkanovic, Hans-Peter Seidel +1
Fractal geometry, defined by self-similar patterns across scales, is crucial for understanding natural structures. This work addresses the fractal inverse problem, which involves e…
Neural Gaussian Scale-Space Fields
Felix Mujkanovic, Ntumba Elie Nsampi, Christian Theobalt +2
Gaussian scale spaces are a cornerstone of signal representation and processing, with applications in filtering, multiscale analysis, anti-aliasing, and many more. However, obtaini…