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20242026
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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

MedGS: Gaussian Splatting for Multi-Modal 3D Medical Imaging

Kacper Marzol, Ignacy Kolton, Weronika Smolak-Dyżewska +6

Endoluminal endoscopic procedures are essential for diagnosing colorectal cancer and other severe conditions in the digestive tract, urogenital system, and airways. 3D reconstructi…

cs.CV2026

ReLAPSe: Reinforcement-Learning-trained Adversarial Prompt Search for Erased concepts in unlearned diffusion models

Ignacy Kolton, Kacper Marzol, Paweł Batorski +3

Machine unlearning is a key defense mechanism for removing unauthorized concepts from text-to-image diffusion models, yet recent evidence shows that latent visual information often…

cs.CV2025

GASP: Gaussian Splatting for Physic-Based Simulations

Piotr Borycki, Weronika Smolak, Joanna Waczyńska +3

Physics simulation is paramount for modeling and utilizing 3D scenes in various real-world applications. However, integrating with state-of-the-art 3D scene rendering techniques su…

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.CV2025

PrAViC: Probabilistic Adaptation Framework for Real-Time Video Classification

Magdalena Trędowicz, Marcin Mazur, Szymon Janusz +3

Video processing is generally divided into two main categories: processing of the entire video, which typically yields optimal classification outcomes, and real-time processing, wh…