3 papers
cs.CV2026
Weakly-Supervised Lung Nodule Segmentation via Training-Free Guidance of 3D Rectified Flow
Richard Petersen, Fredrik Kahl, Jennifer Alvén
Dense annotations, such as segmentation masks, are expensive and time-consuming to obtain, especially for 3D medical images where expert voxel-wise labeling is required. Weakly sup…
cs.CV2025
Addressing degeneracies in latent interpolation for diffusion models
Erik Landolsi, Fredrik Kahl
There is an increasing interest in using image-generating diffusion models for deep data augmentation and image morphing. In this context, it is useful to interpolate between laten…
cs.CV2025
Tiny models from tiny data: Textual and null-text inversion for few-shot distillation
Erik Landolsi, Fredrik Kahl
Few-shot learning deals with problems such as image classification using very few training examples. Recent vision foundation models show excellent few-shot transfer abilities, but…