Synthetic data (Part 2) for "HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields"
Here we provide the data of our article "HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields". It contains the rendered images and the segmentation masks that we use to train our model on HO3Dv2 dataset.
The overall structure of the data is:
├── render_sdf_ho3d.zip - Contains the rendered images for HO3Dv2.
If you find our code, weights, predictions or ideas useful, please cite:
@inproceedings{qi2024hoisdf, title={HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields}, author={Qi, Haozhe and Zhao, Chen and Salzmann, Mathieu and Mathis, Alexander}, booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition}, pages={10392--10402}, year={2024}}
a4165a78-e6e1-47e8-bdd3-28cf8299b326
2024
2.0
CC BY
| Event name | Event acronym | Event place | Event date |
CVPR | Seattle, WA, USA | 2024-06-17 - 2024-06-21 | |
| Relation | Related work | URL/DOI |
Documents | HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields | |
IsSupplementTo | HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields | |
IsVersionOf | Synthetic data (Part 2) for HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields | |