VisBench probes
Collection
Heads fitted on frozen features, one per (task, backbone). Evaluate without training. Each head is valid only against its named backbone. • 20 items • Updated
dinov2_vits14
A trained probe head, not a backbone. It is the small module VisBench fits
on top of frozen dinov2_vits14 features to measure what those features carry.
import visbench
from visbench.hub import load_probe_from_hub
backbone = visbench.get_backbone("dinov2_vits14")
probe = load_probe_from_hub("turhancan97/visbench-surface_normal-dinov2_vits14", backbone=backbone)
These weights were fitted on features from dinov2_vits14, taken with
pooling=mean and feature_mode=dense_only. Loading them against
anything else is refused, because the failure is otherwise silent: a head fitted
on one pooling and fed another has the right shapes and produces a plausible,
wrong number.
| backbone | dinov2_vits14 |
| backbone key | dinov2/dinov2_vits14/224/7764ea0f912e |
| task | surface_normal (mid_level) |
| pooling | mean (requested mean) |
| feature mode | dense_only |
| layers | None |
Reported scores
| metric | value |
|---|---|
d1 |
0.2185 |
d2 |
0.4841 |
d3 |
0.6107 |
mean |
29.4827 |
median |
23.8327 |
rmse |
36.4513 |
Fitted with:
batch_size: 8epochs: 10head: linearhidden_dim: 512layers: Nonelr: 0.0005normal_source: Noneoptimizer: adamwprotocol: probe3duncertainty_aware: Truewarmup_epochs: 1.5weight_decay: 0.0001Generated by VisBench.