############# HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields, CVPR 2024 ############# Haozhe Qi, Chen Zhao, Mathieu Salzmann, Alexander Mathis. Affiliation: EPFL Date: June, 2024 Link to the CVPR article: https://openaccess.thecvf.com/content/CVPR2024/papers/Qi_HOISDF_Constraining_3D_Hand-Object_Pose_Estimation_with_Global_Signed_Distance_CVPR_2024_paper.pdf Link to the Arxiv article: https://arxiv.org/abs/2402.17062 -------------------------------- Here we provide the data of our article "HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields". It contains the preprocessed SDF samples. Meanwhile, we also include rendered data for HO3Dv2 here. The overall structure of the data is: ├── render_sdf_ho3d.zip - Contains the processed SDF files for HO3Dv2 rendered images. ├── train_ho3d.zip - Contains the processed SDF files for HO3Dv2 training set. ├── full_test_dexycb.zip - Contains the processed SDF files for DexYCB full test set. The code to reproduce the results is available at: https://github.com/amathislab/HOISDF -------------------------------- 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}}