DiViNE - Distilling Visual Neural Encoders

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Protocol: 1.0

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Conf -

Conf 0.00 Labels

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PANSt3R controls

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Reconstruction controls

MASt3R max verts: -

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MASt3R pixel stride: -

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Mesh voxel size: -

Mesh triangles: -

Point size 1.6

Performance mode Render on demand Preserve camera

Anny body controls

Tracking

Gate sigma: 3

Max humans: 5

Confirm frames: 10

Coast timeout: 15

Smoothing

Kalman filter

1-euro filter

Phenotype smoothing

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Ground contact

Temporal consistency

Process noise: 1.5

Measurement noise: 0.15

Pose min cutoff: 1.5

Pose beta: 0.5

Pose d-cutoff: 1

Phenotype alpha: 0.4

Phenotype max delta/s: 5

Interpolation

Ghost overlay (raw)

Chase rate: 15

FPS: 0

Overlay settings

Overlay alpha: 0.50

FPS: 0

Depth

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Humans

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Main FPS: 0

Anchor FPS: 0

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Main camera

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© 2025 NAVER LABS Europe

DiViNE demo client for real‑time multi‑modal visual understanding & 3D reconstruction over the DiViNE WebSocket protocol. Internal research & evaluation use only; provided “as is”. DiViNE continues prior efforts UNIC (Universal Classification Models via Multi‑teacher Distillation) and DUNE (Distilling a UNiversal Encoder). Maintained by Mert Bulent Sariyildiz, Philippe Weinzaepfel, Thomas Lucas, Pau De Jorge, Diane Larlus, Yannis Kalantidis, César De Souza, and Martin Humenberger. Project page