activity
20242026
collaborators

7 papers

cs.GR2026

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…

cs.GR2026

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…

cs.CV2026

Beyond Segmentation: Structurally Informed Facade Parsing from Imperfect Images

Maciej Janicki, Aleksander Plocharski, Przemyslaw Musialski

Standard object detectors typically treat architectural elements independently, often resulting in facade parsings that lack the structural coherence required for downstream proced…

cs.GR2026

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…

cs.GR2025

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…

cs.GR2025

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…