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turhancan97/
visbench-keypoints2d-dinov2_vits14

Name: visbench-keypoints2d-dinov2_vits14
Availability: InStock

visbench

probing

keypoints2d

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keypoints2d probe for `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.

python

import visbench
from visbench.hub import load_probe_from_hub

backbone = visbench.get_backbone("dinov2_vits14")
probe = load_probe_from_hub("turhancan97/visbench-keypoints2d-dinov2_vits14", backbone=backbone)

It only works with this 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	`keypoints2d` (low_level)
pooling	`mean` (requested `mean`)
feature mode	`dense_only`
layers	`None`

Reported scores

metric	value
`keypoint_correlation`	0.2356
`mae`	1.1281
`rmse`	2.5472

Reproducing it

Fitted with:

activation: identity
batch_size: 8
epochs: 10
head: linear
hidden_dim: 512
layers: None
loss: l1
lr: 0.0005
optimizer: adamw
protocol: visbench_keypoint2d_regression
warmup_epochs: 1.5
weight_decay: 0.0001

Generated by VisBench.

turhancan97/visbench-keypoints2d-dinov2_vits14

keypoints2d probe for dinov2_vits14

It only works with this backbone

Reproducing it

turhancan97/
visbench-keypoints2d-dinov2_vits14

keypoints2d probe for `dinov2_vits14`