4 papers · 1 filter
ClusterMine: Robust Label-Free Visual Out-Of-Distribution Detection via Concept Mining from Text Corpora
Nikolas Adaloglou, Diana Petrusheva, Mohamed Asker +2
Large-scale visual out-of-distribution (OOD) detection has witnessed remarkable progress by leveraging vision-language models such as CLIP. However, a significant limitation of cur…
Guiding a diffusion model using sliding windows
Nikolas Adaloglou, Tim Kaiser, Damir Iagudin +1
Guidance is a widely used technique for diffusion models to enhance sample quality. Technically, guidance is realised by using an auxiliary model that generalises more broadly than…
Rethinking cluster-conditioned diffusion models for label-free image synthesis
Nikolas Adaloglou, Tim Kaiser, Felix Michels +1
Diffusion-based image generation models can enhance image quality when conditioned on ground truth labels. Here, we conduct a comprehensive experimental study on image-level condit…
Scaling Up Deep Clustering Methods Beyond ImageNet-1K
Nikolas Adaloglou, Felix Michels, Kaspar Senft +2
Deep image clustering methods are typically evaluated on small-scale balanced classification datasets while feature-based -means has been applied on proprietary billion-scale da…