Adapted DINOv2 generalises better than task-specific medical segmentation nets
Only a small part of DINOv2 was adapted; in-distribution U-Nets stayed sharper and caught small lesions more often.
Stories per day · 30 days
Relatedattention1dino1dinov21domain-shift1foundation-models1medical-imaging1self-supervised-learning1vision-transformer1
3 stories, newest first · one card per story
Stories tagged #image-segmentation
Paper trains Vision Transformers to specialize spatial attention heads
Two annotation-free focusing losses steer multi-head attention toward distinct image regions for denser predictions.
Show HN: MultiMatte, a Promptable Image Background Removal Model
Feyn releases MultiMatte, a promptable background-removal model fine-tuned from Meta's SAM 3 via LoRA, outputting alpha mattes that beat SAM 3 on segmentation benchmarks.
7