activity
20242026
collaborators

5 papers

cs.CV2026

TOM-GS: Editable Video Representation via Temporal Opacity Modulation of Static 3D Gaussians

Marek Lisowski, Łukasz Smoliński, Kornel Howil +3

While Implicit Neural Representations (INRs) and dynamic 3D Gaussian Splatting (3DGS) achieve impressive results in video processing, they often fall short of producing representat…

cs.CV2026

OmniStyle-INR: Universal and Multimodal Style Transfer for INRs

Rafał Kajca, Michał Miziołek, Kornel Howil +2

Style transfer remains a fundamental and highly important task across various data modalities, enabling creative manipulation conditioned by both reference images and textual descr…

cs.SD2026

APEX: Audio Prototype EXplanations for Classification Tasks

Piotr Kawa, Kornel Howil, Piotr Borycki +3

Explainable AI (XAI) has achieved remarkable success in image classification, yet the audio domain lacks equally mature solutions. Current methods apply vision-based attribution te…

cs.CV2025

CLIPGaussian: Universal and Multimodal Style Transfer Based on Gaussian Splatting

Kornel Howil, Joanna Waczyńska, Joanna Waczyńska +5

Gaussian Splatting (GS) has recently emerged as an efficient representation for rendering 3D scenes from 2D images and has been extended to images, videos, and dynamic 4D content.…

cs.CV2024

VeGaS: Video Gaussian Splatting

Weronika Smolak-Dyżewska, Dawid Malarz, Kornel Howil +3

Implicit Neural Representations (INRs) employ neural networks to approximate discrete data as continuous functions. In the context of video data, such models can be utilized to tra…