2 citations · 2 across the 17 of their papers we have counts for
12 papers · 1 filter
The Shape of Speech: A Geometric Measure of Coarticulation for Speech-Driven 3D Facial Animation
Danzel Serrano, Przemyslaw Musialski
Speech-driven 3D facial animation can reproduce recognizable mouth poses. However, it can simplify the motion between them, and that motion carries coarticulation, the way the soun…
StippleDiffusion: Capacity-Constrained Stippling using Controlled Diffusion
Ofir Gilad, Aleksander Plocharski, Przemyslaw Musialski +1
Stipple patterns, point sets whose local density tracks a target image, are traditionally produced by per-density iterative optimizers, which are slow, non-differentiable, and must…
STEP-Parts: Geometric Partitioning of Boundary Representations for Large-Scale CAD Processing
Shen Fan, Mikołaj Kida, Przemyslaw Musialski
Many CAD learning pipelines discretize Boundary Representations (B-Reps) into triangle meshes, discarding analytic surface structure and topological adjacency and thereby weakening…
What a Comfortable World: Ergonomic Principles Guided Apartment Layout Generation
Piotr Nieciecki, Aleksander Plocharski, Przemyslaw Musialski
Current data-driven floor plan generation methods often reproduce the ergonomic inefficiencies found in real-world training datasets. To address this, we propose a novel approach t…
A Finite Difference Approximation of Second Order Regularization of Neural-SDFs
Haotian Yin, Aleksander Plocharski, Michal Jan Wlodarczyk +1
We introduce a finite-difference framework for curvature regularization in neural signed distance field (SDF) learning. Existing approaches enforce curvature priors using full Hess…
Scheduling the Off-Diagonal Weingarten Loss of Neural SDFs for CAD Models
Haotian Yin, Przemyslaw Musialski
Neural signed distance functions (SDFs) have become a powerful representation for geometric reconstruction from point clouds, yet they often require both gradient- and curvature-ba…
Joint Neural SDF Reconstruction and Semantic Segmentation for CAD Models
Shen Fan, Przemyslaw Musialski
We propose a simple, data-efficient pipeline that augments an implicit reconstruction network based on neural SDF-based CAD parts with a part-segmentation head trained under PartFi…
Beyond Blur: A Fluid Perspective on Generative Diffusion Models
Grzegorz Gruszczynski, Jakub Meixner, Michal Jan Wlodarczyk +1
We propose a novel PDE-driven corruption process for generative image synthesis based on advection-diffusion processes which generalizes existing PDE-based approaches. Our forward…
FlatCAD: Fast Curvature Regularization of Neural SDFs for CAD Models
Haotian Yin, Aleksander Plocharski, Michal Jan Wlodarczyk +2
Neural signed-distance fields (SDFs) are a versatile backbone for neural geometry representation, but enforcing CAD-style developability usually requires Gaussian-curvature penalti…
Pro-DG: Procedural Diffusion Guidance for Architectural Facade Generation
Aleksander Plocharski, Jan Swidzinski, Przemyslaw Musialski
We use hierarchical procedural rules for the generation of control maps within the stable diffusion framework to produce photo-realistic architectural facade images. Starting from…
Shrinking: Reconstruction of Parameterized Surfaces from Signed Distance Fields
Haotian Yin, Przemyslaw Musialski
We propose a novel method for reconstructing explicit parameterized surfaces from Signed Distance Fields (SDFs), a widely used implicit neural representation (INR) for 3D surfaces.…
FaçAID: A Transformer Model for Neuro-Symbolic Facade Reconstruction
Aleksander Plocharski, Jan Swidzinski, Joanna Porter-Sobieraj +1
We introduce a neuro-symbolic transformer-based model that converts flat, segmented facade structures into procedural definitions using a custom-designed split grammar. To facilita…