1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CV2024★ 1 cited
Image Generation Diversity Issues and How to Tame Them
Mischa Dombrowski, Weitong Zhang, Sarah Cechnicka +2
Generative methods now produce outputs nearly indistinguishable from real data but often fail to fully capture the data distribution. Unlike quality issues, diversity limitations i…
cs.CV2024
Uncovering Hidden Subspaces in Video Diffusion Models Using Re-Identification
Mischa Dombrowski, Hadrien Reynaud, Bernhard Kainz
Latent Video Diffusion Models can easily deceive casual observers and domain experts alike thanks to the produced image quality and temporal consistency. Beyond entertainment, this…
cs.CV2023
Quantifying Sample Anonymity in Score-Based Generative Models with Adversarial Fingerprinting
Mischa Dombrowski, Bernhard Kainz
Recent advances in score-based generative models have led to a huge spike in the development of downstream applications using generative models ranging from data augmentation over…