4 citations · 5 across the 8 of their papers we have counts for
4 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…
UnGuide: Learning to Forget with LoRA-Guided Diffusion Models
Agnieszka Polowczyk, Alicja Polowczyk, Dawid Malarz +4
Recent advances in large-scale text-to-image diffusion models have heightened concerns about their potential misuse, especially in generating harmful or misleading content. This un…
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…
Classifier-free Guidance with Adaptive Scaling
Dawid Malarz, Artur Kasymov, Maciej Zięba +2
Classifier-free guidance (CFG) is an essential mechanism in contemporary text-driven diffusion models. In practice, in controlling the impact of guidance we can see the trade-off b…