surprising because we use a signiﬁcantly simpler predictor. Also, our best model, when evaluated using the
boosted recipe, almost matches the state of the art on Pascal VOC (86.2 versus 89.0 mIoU).
In a ﬁnal experiment, we freeze our backbone, and plug it into a ViT-Adapter Chen et al. (2022) with a
Mask2former head (Cheng et al., 2022). We tune the weights of the adapter and head, but keep the backbone
frozen: only a fraction of the weights are tuned, keeping the training procedure lightweight. We reach 60.2
mIoU on ADE20k, close to the competitive state of the art, standing at 62.9 mIoU (Wang et al., 2022).
DINOv2- Learning Robust Visual Features without Supervision