Figure 2. The entire architecture of our method. We compare the adjusted embeddings, produced by the DINOv2 model, of the positive
and negative support images, with the relevant masks extracted using the SAM model to provide an initial estimate of our segmentation
BBox. We again use DINOv2 for generating pixel-precise heatmaps which provide another estimate for the segmentation. We combine
both these estimates using a binarized overlap to get the final segmentation mask.