EquiDexFlow: Contact-Grounded SE(3)-Equivariant Dexterous Grasp Generative Flows
Paper • 2606.12728 • Published
object_name stringlengths 2 16 | n_grasps int64 4 16 | grasps listlengths 4 16 |
|---|---|---|
A0 | 5 | [
{
"object_name": "A0",
"object_position_mm": [
0,
0,
-3.85281201
],
"object_orientation": [
1,
0,
0,
0
],
"hand_dof_values": [
-0.1177382899091568,
0.47409440971237055,
0.8846346885185647,
1.0541771368348596,
-0.04174239... |
A1 | 13 | [
{
"object_name": "A1",
"object_position_mm": [
0,
0,
-3.86297332
],
"object_orientation": [
1,
0,
0,
0
],
"hand_dof_values": [
-0.017142123728459024,
0.2760755292872701,
1.481317590038696,
0.5582515030869086,
0.292623326... |
A2 | 7 | [
{
"object_name": "A2",
"object_position_mm": [
0,
0,
3.57679813
],
"object_orientation": [
1,
0,
0,
0
],
"hand_dof_values": [
-0.08000651095740018,
0.26059688096979344,
0.9055790159225506,
0.807581055229746,
0.0383679005... |
A3 | 6 | [
{
"object_name": "A3",
"object_position_mm": [
0,
0,
3.8452491800000006
],
"object_orientation": [
1,
0,
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0
],
"hand_dof_values": [
-0.08189589507769533,
0.35041708044096775,
0.8342275882176003,
0.8310505223096506,
-0.... |
A4 | 6 | [
{
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0.5317327547028419,
0.3517445497244212,
1.3801177651576089,
0.0248961484... |
A5 | 11 | [
{
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0... |
A6 | 12 | [
{
"object_name": "A6",
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"hand_dof_values": [
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-... |
B0 | 10 | [
{
"object_name": "B0",
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],
"object_orientation": [
1,
0,
0,
0
],
"hand_dof_values": [
-0.20110044501962276,
-0.18491843235413455,
1.3463348806515976,
1.2505151349109997,
-0.029092... |
B1 | 13 | [
{
"object_name": "B1",
"object_position_mm": [
0,
0,
3.88113579
],
"object_orientation": [
1,
0,
0,
0
],
"hand_dof_values": [
-0.08386552214056009,
0.4892572195140691,
0.6782452396467216,
1.087960935981371,
-0.0575260891... |
B2 | 9 | [
{
"object_name": "B2",
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3.88209932
],
"object_orientation": [
1,
0,
0,
0
],
"hand_dof_values": [
-0.10289914114765246,
0.8211967485277706,
0.021535109874696187,
1.6030295037376734,
0.02227660... |
B3 | 14 | [
{
"object_name": "B3",
"object_position_mm": [
0,
0,
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],
"object_orientation": [
1,
0,
0,
0
],
"hand_dof_values": [
-0.17025647539008515,
0.17860211057819614,
1.185388450207614,
1.447774841715741,
0.1073697792... |
B4 | 10 | [
{
"object_name": "B4",
"object_position_mm": [
0,
0,
3.86372914
],
"object_orientation": [
1,
0,
0,
0
],
"hand_dof_values": [
-0.021228383692945482,
0.07685190791454515,
1.636144790042893,
-0.20701432919365165,
0.2003855... |
End of preview. Expand in Data Studio
EquiDexFlow Grasps — DexGraspDB (test split)
811 grasps per hand for the Allegro and LEAP hands, one JSON per object with a nested grasps: [...] array.
Layout
allegro/*.json— 81 files, 811 graspsleap/*.json— 81 files, 811 grasps
Schema
Full per-grasp field table (fields, shapes, units, frame conventions, minimum viable record): see data/README.md in the EquiDexFlow GitHub repo.
Loading
from huggingface_hub import snapshot_download
path = snapshot_download("cenwerem/equidexflow-grasps", repo_type="dataset")
# then point DexGraspDBDataset at path/allegro or path/leap
Citation
If you find the dataset here useful in your work, please cite us using the following BiBTeX entry:
@article{enwerem_equidexflow_2026,
author = {Enwerem, Clinton and Baras, John S. and Belta, Calin},
title = {{EquiDexFlow}: Contact-Grounded {SE}(3)-Equivariant Dexterous Grasp Generative Flows},
year = {2026},
doi = {10.48550/arXiv.2606.12728},
number = {{arXiv}:2606.12728},
publisher = {{arXiv}},
date = {2026-06-10},
eprinttype = {arxiv},
eprint = {2606.12728 [cs.RO]},
shorttitle = {{EquiDexFlow}},
url = {http://arxiv.org/abs/2606.12728}
}
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