DINOv2

A team of researchers has developed a training-free multi-signal segmentation pipeline for the CVPR 2026 UG2+ Challenge's Dynamic Object Segmentation in Turbulence (DOST) track. The system combines RA…

Researchers have developed representation-conditioned diffusion models that generate synthetic training images by conditioning on learned representations from DINOv2, DINOv3, and CLIP, achieving a 10.…

Researchers demonstrated that multi-level Floyd-Steinberg error-diffusion dithering, a lightweight input transformation, can disrupt adversarial attacks against vision foundation models while preservi…