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20242026
most citedMiraGe: Editable 2D Images using Gaussian Splatting

1 citations · 1 across the 5 of their papers we have counts for

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cs.LG2025

Memory Self-Regeneration: Uncovering Hidden Knowledge in Unlearned Models

Agnieszka Polowczyk, Alicja Polowczyk, Joanna Waczyńska +2

The impressive capability of modern text-to-image models to generate realistic visuals has come with a serious drawback: they can be misused to create harmful, deceptive or unlawfu…

cs.GR2025

GS-Verse: Mesh-based Gaussian Splatting for Physics-aware Interaction in Virtual Reality

Anastasiya Pechko, Piotr Borycki, Joanna Waczyńska +4

As the demand for immersive 3D content grows, the need for intuitive and efficient interaction methods becomes paramount. Current techniques for physically manipulating 3D content…

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

HuSc3D: Human Sculpture dataset for 3D object reconstruction

Weronika Smolak-Dyżewska, Dawid Malarz, Grzegorz Wilczyński +4

3D scene reconstruction from 2D images is one of the most important tasks in computer graphics. Unfortunately, existing datasets and benchmarks concentrate on idealized synthetic o…

cs.CV2025

EPIC: Explanation of Pretrained Image Classification Networks via Prototype

Piotr Borycki, Magdalena Trędowicz, Szymon Janusz +4

Explainable AI (XAI) methods generally fall into two categories. Post-hoc approaches generate explanations for pre-trained models and are compatible with various neural network arc…