76 citations · 257 across the 98 of their papers we have counts for
20 papers · 1 filter
From Unlearning to UNBRANDING: A Benchmark for Trademark-Safe Text-to-Image Generation
Dawid Malarz, Filip Manjak, Maciej Zięba +2
The rapid progress of text-to-image diffusion models raises significant concerns regarding the unauthorized reproduction of trademarked content. While prior work targets general co…
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…
AEGIS: Preserving privacy of 3D Facial Avatars with Adversarial Perturbations
Dawid Wolkiewicz, Anastasiya Pechko, Przemysław Spurek +1
The growing adoption of photorealistic 3D facial avatars, particularly those utilizing efficient 3D Gaussian Splatting representations, introduces new risks of online identity thef…
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…
GaINeR: Geometry-Aware Implicit Network Representation
Weronika Jakubowska, Mikołaj Zieliński, Rafał Tobiasz +4
Implicit Neural Representations (INRs) are widely used for modeling continuous 2D images, enabling high-fidelity reconstruction, super-resolution, and compression. Architectures su…
InTAct: Interval-based Task Activation Consolidation for Continual Learning
Patryk Krukowski, Jan Miksa, Piotr Helm +3
Continual learning is a fundamental challenge in artificial intelligence that requires networks to acquire new knowledge while preserving previously learned representations. Despit…