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cs.CV2026
DINO-QPM: Adapting Visual Foundation Models for Globally Interpretable Image Classification
Robert Zimmermann, Thomas Norrenbrock, Bodo Rosenhahn
Although visual foundation models like DINOv2 provide state-of-the-art performance as feature extractors, their complex, high-dimensional representations create substantial hurdles…
cs.CV2026
Video Patch Pruning: Efficient Video Instance Segmentation via Early Token Reduction
Patrick Glandorf, Thomas Norrenbrock, Bodo Rosenhahn
Vision Transformers (ViTs) have demonstrated state-ofthe-art performance in several benchmarks, yet their high computational costs hinders their practical deployment. Patch Pruning…