The paper reports that DINOv2 produces dense feature artifacts that impair its ability to capture fine-grained details, resulting in abnormal representations dominated by global context. This is measured via unsupervised segmentation with CAUSE: DINOv2 achieves 29.9 mIoU on Cityscapes and 43.0 mIoU on COCO-Stuff. Affinity map visualizations (Figure 8) show that a query token's similarity map is spread broadly rather than focused on the local region, confirming the global-context dominance. The paper attributes this observation to Darcet et al. 2023.
Evidence
observational
Key metric
DINOv2 mIoU: 29.9 on Cityscapes, 43.0 on COCO-Stuff (Table 5)
Caveat
The interpretation of the artifacts as 'register tokens' is attributed to Darcet et al. 2023; this paper measures the performance but does not independently diagnose the mechanism.