CLARU
Cloth-splatters2026MIT

DexGarmentLab Lift Correspondence 2026-08-22

A point-cloud dataset of 1,800 successful garment lift/manipulation episodes with dense surface correspondence annotations, spanning tops, dresses, and trousers. Each episode contains up to 16 observations with 2,048 XYZ points and persistent surface-template IDs for cloth manipulation research.

Downloads0
Episodes1800

Why This Matters for Physical AI

This dense point-cloud correspondence dataset enables training of cloth state estimation and manipulation models by providing ground-truth surface tracking across deformation phases.

Technical Profile

Modalities
point_cloud
Environment
lab
Task Types
manipulationcloth-manipulationgrasping
Episodes
1800
Data Format
NumPy
Annotation Types
semantic_keypoint_correspondencessurface_template_idsvisibility_distancesgrasp_phase_labels
License
MIT
Part of the DexGarmentLab family

Access

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