2 citations · 2 across the 17 of their papers we have counts for
19 papers
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…
The Token Is a Group Element: On Lie-Algebra Attention over Matrix Lie Groups
Przemyslaw Musialski
We place the attention token on the group: a token is an element of a matrix Lie group -- a bare transformation, with no feature payload and no external action car…
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…
INST-Align: Implicit Neural Alignment for Spatial Transcriptomics via Canonical Expression Fields
Bonian Han, Cong Qi, Przemyslaw Musialski +1
Spatial transcriptomics (ST) measures mRNA expression while preserving spatial organization, but multi-slice analysis faces two coupled difficulties: large non-rigid deformations a…
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…
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…
HOSC: A Periodic Activation with Saturation Control for High-Fidelity Implicit Neural Representations
Michal Jan Wlodarczyk, Danzel Serrano, Przemyslaw Musialski
Periodic activations such as sine preserve high-frequency information in implicit neural representations (INRs) through their oscillatory structure, but often suffer from gradient…
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…
Neural Surface Priors for Editable Gaussian Splatting
Jakub Szymkowiak, Weronika Jakubowska, Dawid Malarz +5
In computer graphics and vision, recovering easily modifiable scene appearance from image data is crucial for applications such as content creation. We introduce a novel method tha…
Optimizing 3D Geometry Reconstruction from Implicit Neural Representations
Shen Fan, Przemyslaw Musialski
Implicit neural representations have emerged as a powerful tool in learning 3D geometry, offering unparalleled advantages over conventional representations like mesh-based methods.…
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…
HOSC: A Periodic Activation Function for Preserving Sharp Features in Implicit Neural Representations
Danzel Serrano, Jakub Szymkowiak, Przemyslaw Musialski
Recently proposed methods for implicitly representing signals such as images, scenes, or geometries using coordinate-based neural network architectures often do not leverage the ch…